{ "data": { "a": { "slug": "mini-swe-agent", "name": "mini-swe-agent", "vendor": "SWE-bench team (Princeton and Stanford)", "vendorUrl": "https://mini-swe-agent.com", "kind": "harness", "category": "agent-harnesses", "summary": "Minimal open-source coding agent from the Princeton and Stanford team behind SWE-bench, shipped as the `mini` CLI and a Python library. It gives the model one bash tool, works with any model through LiteLLM, and is a common SWE-bench baseline.", "url": "https://www.anchorterminal.com/tools/mini-swe-agent", "markdownUrl": "https://www.anchorterminal.com/tools/mini-swe-agent.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mini-swe-agent.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mini-swe-agent.json", "dns": "mini-swe-agent.grade.anchorterminal.com", "repo": "https://github.com/SWE-agent/mini-swe-agent", "license": "MIT", "transports": [], "packages": [ { "registry": "pypi", "name": "mini-swe-agent" } ], "auth": "none", "authNotes": "No account of its own. A model key goes in an environment variable or the global `.env` file that `mini-extra config setup` writes, and is passed to the provider through LiteLLM, OpenRouter, Portkey or Requesty. Local models work through LiteLLM's `api_base`.", "pricing": "free", "pricingNotes": "Free and MIT, with nothing to buy. The owner pays the model provider, or nothing with a local model. Each run stops at a $3 cost limit by default, and a local model needs `MSWEA_COST_TRACKING=ignore_errors`.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-18).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 8600, "npmWeekly": null, "pypiWeekly": 4437981, "asOf": "2026-10-18" }, "docsUrl": "https://mini-swe-agent.com/latest/", "capabilities": [ "agent.harness" ], "tags": [ "harness", "coding-agent", "cli", "open-source", "python", "free", "no-card", "local", "docker" ], "lastRelease": "2026-07-23", "graded": true, "anchor": { "graded": true, "score": 59, "grade": "C", "agentReady": false, "rank": 647, "ranked": true, "rankOf": 1354, "categoryRank": 18, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 69, "maintenance": 32, "payments": 60, "reliability": 65, "schema": 58, "security": 58, "transparency": 56 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "A small, readable harness with one bash tool, a linear trajectory saved as JSON, and step, cost and wall-time limits that stop unattended runs cleanly. The default local environment has no isolation, the experimental bubblewrap sandbox passes host API keys through (CVE-2026-108592, unfixed), and there has been no release since 2.4.6 on 23 July 2026.", "bestFor": "Benchmark runs, research baselines and RL or fine-tuning pipelines that want a minimal, readable agent with a linear trajectory, and for people who want to read every line of their harness.", "strengths": [ "MIT, with an agent class of about 190 lines that a reviewer can read in one sitting", "Step, cost ($3 by default) and wall-time limits, each ending the run with its own exit status in the trajectory", "Any model through LiteLLM, OpenRouter, Portkey or Requesty, local ones included, with no account", "Docker, Podman and Singularity environments, where the Docker one forwards no host variables unless listed", "No telemetry found in the source" ], "weaknesses": [ "The default local environment runs commands on the host with no isolation and the full host environment", "CVE-2026-108592, published 10 October 2026, leaves the experimental bubblewrap sandbox passing host API keys and network through, unfixed in 2.4.6", "No release since 2.4.6 on 23 July 2026, nothing merged into main since 17 August, and 77 of the 85 pull requests numbered after #917 still open", "No MCP client, no ACP and no server mode", "No changelog file, and the PyPI classifier still says 3 - Alpha at 2.4.6" ], "agentNotes": [ "Run with `-y --exit-immediately` for unattended use. Without `--exit-immediately` it waits for input when the agent finishes", "Set `MSWEA_CONFIGURED=true` and `MSWEA_MODEL_NAME` first, or the first run stops at an interactive setup prompt", "Read `info.exit_status` in the `-o` trajectory file. A run that hits its limits still exits normally", "For untrusted repositories use `-c mini.yaml -c environment.environment_class=docker -c environment.image=\u003cimage\u003e`. The local and bubblewrap environments both expose host variables", "Strip model keys from the environment commands see, since the local environment passes every host variable to each command" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 59 } ], "editorialScores": { "ergonomics": 69, "maintenance": 32, "payments": 60, "reliability": 65, "schema": 58, "security": 58, "transparency": 62 }, "provenanceScore": 50, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install mini-swe-agent # or: uvx mini-swe-agent", "headless": { "command": "mini -t \"$TASK\" -y --exit-immediately -m \u003cprovider/model\u003e -l 3 -o run.traj.json", "env": { "ANTHROPIC_API_KEY": "\u003ckey\u003e", "MSWEA_CONFIGURED": "true" } } }, "letme": { "capability": "https://letme.dev/agent.harness", "tool": "https://letme.dev/mini-swe-agent" }, "area": "frameworks", "provenance": { "legalEntity": "No legal entity named. The MIT licence names Kilian A. Lieret and Carlos E. Jimenez", "domain": "mini-swe-agent.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "The docs site is GitHub Pages built from the repository. It has no terms, privacy policy or security.txt (/.well-known/security.txt returned 404 on 18 October 2026).", "The security page names four contacts at Princeton and Stanford by email, with no response time.", "The repository has no changelog file and tags carry only a version bump. Release notes, if any, are on GitHub releases, which we couldn't read because GitHub's web pages refused this run (18 October and 4 November)." ], "score": 50 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mini-swe-agent.json", "live": { "slug": "mini-swe-agent", "versions": [ { "registry": "github", "name": "SWE-agent/mini-swe-agent", "version": "v2.4.6", "released": "2026-07-23", "seenAt": "2026-11-05T21:48:08.95087274Z" }, { "registry": "pypi", "name": "mini-swe-agent", "version": "2.4.6", "released": "2026-07-23", "seenAt": "2026-11-05T21:48:07.790301857Z" } ], "githubStars": 9109, "pypiWeekly": 3615487, "securityTxt": { "url": "https://mini-swe-agent.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-05T15:56:07.297685501Z" }, "domain": { "domain": "mini-swe-agent.com", "registered": "2025-07-23", "source": "https://rdap.verisign.com/com/v1/domain/mini-swe-agent.com", "checkedAt": "2026-11-01T14:12:26.696049173Z" }, "github": { "repo": "swe-agent/mini-swe-agent", "checkedAt": "2026-11-02T09:29:40.130801973Z", "stars": 9031, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-26T22:39:14Z", "openIssues": 45, "openPRs": 88, "issuesOpened90d": 33, "issuesClosed90d": 2, "prsMerged90d": 1, "ci": { "branch": "main", "runs": 50, "success": 48, "failure": 2, "other": 0, "latest": "success", "latestAt": "2026-09-03T05:06:48Z" }, "replies": { "sampled": 25, "unanswered": 23, "medianDays": 7.8 } }, "updatedAt": "2026-11-05T21:48:08.95087274Z" } }, "answer": "OpenAI Agents API scores 73.3 (BB) on agent readiness against mini-swe-agent's 59 (C), and leads in 5 of 7 scored categories. mini-swe-agent leads on reliability and payments \u0026 pricing.", "b": { "slug": "openai-agents-api", "name": "OpenAI Agents API", "vendor": "OpenAI", "vendorUrl": "https://openai.com/index/introducing-the-agents-api/", "kind": "http-api", "category": "agent-harnesses", "summary": "The OpenAI Agents API runs OpenAI's managed Codex harness as a hosted service. One call creates a session with a model, tools, MCP servers, subagents and an OpenAI-hosted or self-hosted sandbox, and OpenAI runs the loop.", "url": "https://www.anchorterminal.com/tools/openai-agents-api", "markdownUrl": "https://www.anchorterminal.com/tools/openai-agents-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/openai-agents-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/openai-agents-api.json", "dns": "openai-agents-api.grade.anchorterminal.com", "license": "Proprietary hosted API under OpenAI's Services Agreement. The SDKs are Apache 2.0", "transports": [ "https" ], "remoteUrl": "https://api.openai.com/v1/agents/sessions", "packages": [ { "registry": "pypi", "name": "openai" }, { "registry": "npm", "name": "openai" } ], "auth": "api-key", "authNotes": "An OpenAI project API key as a Bearer token, with the header `OpenAI-Beta: agents=v1`. Project keys can be restricted per endpoint or read-only, and service accounts and workload identity federation are available, per the openai-api listing. Signing up and creating a key need a person in a browser.", "pricing": "usage", "pricingNotes": "No fee for the API itself. Model tokens are billed at the chosen model's API rates, OpenAI tools at their built-in rates (web search $10.00 per 1,000 calls plus content tokens), and OpenAI-hosted sandboxes at container rates, $0.03 for 1 GB, $0.12 for 4 GB, $0.48 for 16 GB and $1.92 for 64 GB per 20-minute session, billed by the minute with a 5-minute minimum. Since 9 October sandbox compute is billed only during active turns (checked 2026-11-06).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Agents API guides or on OpenAI's pricing page; billing is to an OpenAI account (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://developers.openai.com/api/docs/guides/agents-api/overview", "llmsTxt": "https://developers.openai.com/api/docs/llms.txt", "capabilities": [ "agent.harness" ], "tags": [ "official", "hosted", "beta", "usage-priced", "llms-txt", "status-page", "mcp-client", "sandbox", "subagents", "webhooks", "soc2", "iso27001", "bug-bounty" ], "lastRelease": "2026-10-16", "graded": true, "anchor": { "graded": true, "score": 73.3, "grade": "BB", "agentReady": true, "rank": 99, "ranked": true, "rankOf": 1354, "categoryRank": 2, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 80, "maintenance": 87, "payments": 30, "reliability": 60, "schema": 88, "security": 87, "transparency": 85 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "OpenAI's hosted agent runtime, the Codex harness behind one session call, with MCP, functions, web search, computer use, subagents and sandboxes on OpenAI or your own infrastructure. Documentation, errors and SDKs are thorough. It's still public beta, can't use Zero Data Retention and keeps data in the United States only.", "bestFor": "Teams that want OpenAI to run the agent loop, with sandboxes, MCP tools and subagents, and are fine with a beta API, US-only data residency and no Zero Data Retention.", "strengths": [ "One session call configures the model, tools, MCP servers, subagents and the sandbox, and OpenAI runs and recovers the loop", "Sandboxes on OpenAI or self-hosted, with guides for ten providers including E2B, Daytona, Modal, Cloudflare and Vercel", "An errors guide with codes per status and turn, Retry-After and a check-before-retry procedure", "Webhooks, streamed events, tracing and usage views for each session", "SDK examples in Python, JavaScript, Go, Java and Ruby", "Status page with its own Agents component" ], "weaknesses": [ "Public beta since 10 September 2026 behind the agents=v1 beta header, with no GA date", "Not eligible for Zero Data Retention, and data residency is United States only", "No idempotency key for session or turn requests; retries depend on checking state first", "One API-wide major outage on 29 September included it, plus several smaller incidents since release", "No retention period stated for published artifacts after a sandbox expires" ], "agentNotes": [ "POST https://api.openai.com/v1/agents/sessions with a project key and the header OpenAI-Beta: agents=v1, or use client.beta.agents in the SDKs", "Before retrying, retrieve the session and turn and check which actions completed, since there's no idempotency key", "Set the sandbox network to restricted with an allowlist of up to 100 hosts when the agent doesn't need the open web", "Save files from /workspace/outputs before deleting a session; no retention period is stated for artifacts", "Don't send data that needs Zero Data Retention or non-US residency; the Agents API supports neither" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 73.3 } ], "editorialScores": { "ergonomics": 80, "maintenance": 87, "payments": 30, "reliability": 60, "schema": 88, "security": 87, "transparency": 75 }, "provenanceScore": 95, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://api.openai.com/v1/agents/sessions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: agents=v1\" \\\n -H \"Content-Type: application/json\" \\\n -d @session.json # model, tools, environment and input, per the quickstart" }, "letme": { "capability": "https://letme.dev/agent.harness", "tool": "https://letme.dev/openai-agents-api" }, "sameCompany": [ "openai-api", "openai-embeddings", "openai-guardrails", "openai-moderation", "openai-image-api", "openai-sora", "openai-speech-to-text", "gpt-live", "openai-realtime", "openai-agents-sdk", "openai-decisions-api", "openai-codex", "gpt-oss-120b", "gpt-oss-20b" ], "area": "frameworks", "provenance": { "legalEntity": "OpenAI OpCo, LLC", "domain": "openai.com", "domainRegistered": "2007-01-19", "domainNote": "openai.com was registered in 2007, before OpenAI existed, per the openai-api listing.", "endpointOnVendorDomain": true, "terms": "https://openai.com/policies/services-agreement/", "privacy": "https://openai.com/policies/privacy-policy/", "statusPage": "https://status.openai.com", "changelog": "https://developers.openai.com/api/docs/changelog", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "The endpoint is on api.openai.com, the same host as the rest of the OpenAI API. Terms, privacy, security.txt and the domain are the openai-api listing's readings." ], "score": 95 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/openai-agents-api.json", "live": { "slug": "openai-agents-api", "probe": { "target": "https://api.openai.com/v1/agents/sessions", "method": "get", "lastAt": "2026-11-06T09:47:41.371658489Z", "lastOk": true, "lastStatus": 400, "lastMs": 162, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 148, "p95ms24h": 166, "samples24h": 47, "samples30d": 47, "days": [ { "date": "2026-11-06", "probes": 47, "ok": 47 } ] }, "vendorStatus": { "page": "https://status.openai.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-06T09:43:26.425829944Z" }, "updatedAt": "2026-11-06T09:47:41.371658489Z" } }, "edges": [ { "by": 55, "category": "maintenance", "leads": "openai-agents-api", "name": "Maintenance \u0026 community", "reasons": { "a": "2.4.6 on PyPI on 2026-07-23, 104 days before this check, and still the newest tag (10). No release in the 90 days to 4 November (0). Main hasn't moved since 3 September (three commits since 23 July, one from pre-commit-ci). Outside fixes were merged within days through July, but no pull request has been merged since #917 (17 August), 77 of the 85 pull requests numbered after it still carry open merge refs on the git remote, and maintainer reply times couldn't be read; the 18 October shields.io counts are struck (5). The Python library ships in the same package as the CLI and is current (10). Dependabot and pre-commit-ci run, and CI workflows exist with their current state unconfirmed (7).", "b": "Closed API. Last dated change 16 October 2026, Ultrafast mode and document skills (30). Four dated changelog entries in the 57 days since release, 10 September, 29 September, 9 October and 16 October (20). Changelog and help centre, as the openai-api listing reads them (12 of 15). Official SDKs carry beta.agents (15). SDK CI, per the openai-api listing (10). 30 + 20 + 12 + 15 + 10 = 87." }, "scores": { "a": 32, "b": 87 } }, { "by": 30, "category": "schema", "leads": "openai-agents-api", "name": "Schema \u0026 documentation", "reasons": { "a": "Framework reading. Typed pydantic config classes, typed protocols for agents, models and environments, `py.typed`, a mkdocstrings API reference and a documented trajectory format, but no machine-readable spec for configs or output (15). No llms.txt (/latest/llms.txt and /llms.txt returned 404). The docs are Markdown in the repository, readable raw, though they rely on build-time includes (3). The FAQ and environments page say when to pick mini over SWE-agent and which environment isolates, but the FAQ still says it doesn't use tool calls while the v2 guide says tool calls are now the default (12). Modes are a typed Literal and limits are typed fields, while `model_kwargs` passes free-form to LiteLLM (10). Hello-world and cookbook examples, a model troubleshooting page and a partial list of exit statuses (11). A dated v2 migration guide and kept v1 docs, with release notes only on GitHub, which we couldn't read (7).", "b": "The reference is linked from the overview and the SDKs carry beta.agents types; we didn't confirm /agents/sessions in OpenAI's public OpenAPI file, so 15 of 25. llms.txt with every Agents API page and Markdown twins (10). The overview, architecture page and the agents guide that compares the Agents API, Agents SDK and Responses API say when to use it (20). Typed configuration with enumerated container sizes, network modes and environment types (13 of 15). Examples in six languages and an errors page with codes per HTTP status, turn and session (15). Dated changelog entries and a versioned beta header (15). 15 + 10 + 20 + 13 + 15 + 15 = 88." }, "scores": { "a": 58, "b": 88 } }, { "by": 30, "category": "payments", "leads": "mini-swe-agent", "name": "Payments \u0026 pricing", "reasons": { "a": "Self-hosted rule. No payment protocol (0). Free under MIT with nothing to buy (20). No card or account for the software, and it runs against a local model (20). An agent can install it from PyPI and run a task with no sign-up, given a model endpoint (20).", "b": "No machine payment protocol (0). Model, tool and container prices published without a login, and no fee for the API itself (20). The Free tier reading of the openai-api listing, half (10). Sign-up in a browser (0). 0 + 20 + 10 + 0 = 30." }, "scores": { "a": 60, "b": 30 } }, { "by": 29, "category": "security", "leads": "openai-agents-api", "name": "Security \u0026 auth", "reasons": { "a": "Harness reading of the framework checklist, used for every harness in this batch. 30 for what leaves the machine by default, 20 for approvals and sandboxing, 15 for prompt-injection posture, 15 for audit and 20 for the security programme. No telemetry in mini's own source, and prompts go only to the configured provider. LiteLLM's own network behaviour wasn't checked (28). The CLI asks before each command by default, with regex whitelists and `-y` to skip, but the Python `DefaultAgent` never asks, the default local environment has no isolation and passes the full host environment to every command, and the experimental bubblewrap sandbox leaks host variables and shares the network (CVE-2026-108592). Docker forwards no host variables unless listed (8). No prompt-injection guidance found (2). A full trajectory of every command and output saved as JSON after each step, and a trajectory inspector (13). A security policy (docs/SECURITY.md) naming four maintainers to contact by email, with no response time, which meets the disclosure-policy reading at 7 as for cowagent and tokenrip. No bounty or advisory page, and CVE-2026-108592 (VulnCheck, 10 October) still has no fix in any release or on main. Compromised LiteLLM 1.82.7 and 1.82.8 are excluded in the dependency pins since 24 March 2026 (#794) (7).", "b": "Project keys with restricted per-endpoint permissions, service accounts and workload identity, per the openai-api listing; we didn't confirm a key can be limited to /v1/agents (27 of 30). Automatic review for approvals, a sandbox network restricted to a host allowlist, vaults for secrets and a sandbox security guide (17 of 20). The agent reads web pages, MCP results and browser content; the sandbox security guide and approval flow are the mitigations, with no prompt-injection guide of its own found (8 of 15). Tracing, observability and usage per session and admin audit logs (15). SOC 2 Type 2, ISO 27001 family, Bugcrowd bounty and a disclosure policy, per the openai-api listing (20). Not ZDR-eligible and US residency only, recorded under transparency. 27 + 17 + 8 + 15 + 20 = 87." }, "scores": { "a": 58, "b": 87 } }, { "by": 29, "category": "transparency", "leads": "openai-agents-api", "name": "Transparency \u0026 trust", "reasons": { "a": "MIT (30). No privacy policy, terms or data-handling statement, though the tool runs locally and collects nothing we could find (8). A v2 migration guide marks the breaking changes, says how to pin `mini-swe-agent~=1.0`, and keeps v1 docs and a v1 branch, but there's no deprecation policy or end date for v1 (10). No telemetry in the source, but the docs don't say so (14).", "b": "Closed service with clear terms, Apache-2.0 SDKs (15). Session state retained until deleted, deletable sessions and artifacts, not ZDR-eligible, US residency only, and the data-controls guide agrees; no retention period for artifacts after a sandbox expires (25 of 30). Dated deprecation notices with minimum periods for GA models; a beta API can change faster (15 of 20). Subprocessors and processing countries listed, per the openai-api listing (20). 15 + 25 + 15 + 20 = 75." }, "scores": { "a": 56, "b": 85 } }, { "by": 11, "category": "ergonomics", "leads": "openai-agents-api", "name": "Agent ergonomics", "reasons": { "a": "Harness reading of the framework line, scored on what an agent or pipeline driving it has to supply. One bash tool and a short system prompt, with output over 10,000 characters cut to its first and last 5,000, but no compaction of a long history (22). Step, cost and wall-time limits, global call and cost limits by environment variable, and a 30-second timeout per command (18). The trajectory JSON records Submitted, LimitsExceeded, TimeExceeded or RepeatedFormatError, but stdout is human-readable only and these aren't process exit codes (12). Model calls retry ten times with exponential backoff, and the trajectory is saved after every step, but there's no resume and no undo (8). Python bindings only. An unattended `mini` run needs `-y`, `--exit-immediately` and `MSWEA_CONFIGURED`, the last found only in the source (9). No MCP client, ACP or server mode.", "b": "Read as an API an agent drives. Context is compacted automatically, and session budgets and streamed events keep output sized (20 of 25). Sessions can be listed, continued and steered, events streamed or sent by webhook, artifacts fetched (15 of 20). Actionable error codes with recovery steps (20). No idempotency key; a documented check-then-retry procedure (10 of 20). One session call with defaults (medium sandbox, network enabled), SDKs in five languages (15). 20 + 15 + 20 + 10 + 15 = 80." }, "scores": { "a": 69, "b": 80 } } ], "facts": [ { "a": "Agent harness", "b": "HTTP API", "name": "Kind" }, { "a": "SWE-bench team (Princeton and Stanford)", "b": "OpenAI", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.openai.com/v1/agents/sessions", "name": "Hosted endpoint" }, { "a": "", "b": "https", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "MIT", "b": "Proprietary hosted API under OpenAI's Services Agreement. The SDKs are Apache 2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-07-23", "b": "2026-10-16", "name": "Last release" }, { "a": "no document linked", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "no document linked", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "not read yet", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "8.6k stars, 4.4M PyPI/wk", "b": "none", "name": "Popularity" }, { "a": "3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "OpenAI Agents API scores 73.3 (BB) on agent readiness against mini-swe-agent's 59 (C), and leads in 5 of 7 scored categories. mini-swe-agent leads on reliability and payments \u0026 pricing.", "question": "Which is better for AI agents, mini-swe-agent or OpenAI Agents API?" }, { "answer": "No hosted endpoint is listed for mini-swe-agent. OpenAI Agents API has a hosted endpoint at https://api.openai.com/v1/agents/sessions.", "question": "Can an agent call mini-swe-agent and OpenAI Agents API without installing anything?" }, { "answer": "mini-swe-agent is open source (MIT). No open-source release is listed for OpenAI Agents API.", "question": "Are mini-swe-agent and OpenAI Agents API open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 65 against 60", "Payments \u0026 pricing, 60 against 30" ], "also": [ "No key needed to call it", "Free to start without a card", "Open source" ], "goodFor": "Benchmark runs, research baselines and RL or fine-tuning pipelines that want a minimal, readable agent with a linear trajectory, and for people who want to read every line of their harness.", "slug": "mini-swe-agent", "watchFor": "The default local environment runs commands on the host with no isolation and the full host environment" }, { "aheadOn": [ "Schema \u0026 documentation, 88 against 58", "Agent ergonomics, 80 against 69", "Security \u0026 auth, 87 against 58", "Maintenance \u0026 community, 87 against 32", "Transparency \u0026 trust, 85 against 56" ], "also": [ "Agent-ready, a grade of BB or better", "A hosted endpoint, with nothing to install" ], "goodFor": "Teams that want OpenAI to run the agent loop, with sandboxes, MCP tools and subagents, and are fine with a beta API, US-only data residency and no Zero Data Retention.", "slug": "openai-agents-api", "watchFor": "Public beta since 10 September 2026 behind the agents=v1 beta header, with no GA date" } ], "history": { "mini-swe-agent": [ { "causes": [ "evidence", "correction", "time" ], "date": "2026-11-04", "delta": 1.9, "from": 57.1, "fromGrade": "C", "to": 59, "toGrade": "C" }, { "causes": [ "evidence" ], "date": "2026-10-27", "delta": 0.4, "from": 56.7, "fromGrade": "C", "to": 57.1, "toGrade": "C" } ], "openai-agents-api": null }, "job": { "capability": "agent.harness", "name": "Agent harnesses" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agent-zero-vs-mini-swe-agent.json", "title": "Agent Zero vs mini-swe-agent", "url": "https://www.anchorterminal.com/compare/agent-zero-vs-mini-swe-agent" }, { "json": 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"https://www.anchorterminal.com/compare/mini-swe-agent-vs-unstoppable.json", "title": "mini-swe-agent vs Unstoppable", "url": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-unstoppable" }, { "json": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-vibe-trading.json", "title": "mini-swe-agent vs Vibe-Trading", "url": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-vibe-trading" }, { "json": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-warp.json", "title": "mini-swe-agent vs Warp (Warp Agent CLI and the Oz Agent API)", "url": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-warp" }, { "json": "https://www.anchorterminal.com/compare/minimax-code-vs-openai-agents-api.json", "title": "MiniMax Code vs OpenAI Agents API", "url": "https://www.anchorterminal.com/compare/minimax-code-vs-openai-agents-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-vibe-cli-vs-openai-agents-api.json", "title": "Mistral Vibe CLI vs OpenAI Agents 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"https://www.anchorterminal.com/compare/openai-agents-api-vs-openmausbot.json", "title": "OpenAI Agents API vs OpenMausBot", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-openmausbot" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-api-vs-prime-agent.json", "title": "OpenAI Agents API vs Prime Agent", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-prime-agent" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-api-vs-qoder-cli.json", "title": "OpenAI Agents API vs Qoder CLI", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-qoder-cli" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-api-vs-qwen-code.json", "title": "OpenAI Agents API vs Qwen Code", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-qwen-code" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-api-vs-reflection-mirror.json", "title": "OpenAI Agents API vs Mirror CLI", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-reflection-mirror" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-api-vs-rovo-dev-cli.json", "title": "OpenAI Agents API vs Rovo Dev CLI", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-rovo-dev-cli" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-api-vs-unstoppable.json", "title": "OpenAI Agents API vs Unstoppable", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-unstoppable" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-api-vs-vibe-trading.json", "title": "OpenAI Agents API vs Vibe-Trading", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-vibe-trading" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-api-vs-warp.json", "title": "OpenAI Agents API vs Warp (Warp Agent CLI and the Oz Agent API)", "url": "https://www.anchorterminal.com/compare/openai-agents-api-vs-warp" } ], "panel": null, "scores": [ { "by": 5, "edge": "mini-swe-agent", "key": "reliability", "mini-swe-agent": 65, "name": "Reliability", "openai-agents-api": 60, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 30, "edge": "openai-agents-api", "key": "schema", "mini-swe-agent": 58, "name": "Schema \u0026 documentation", "openai-agents-api": 88, "weight": 13 }, { "by": 11, "edge": "openai-agents-api", "key": "ergonomics", "mini-swe-agent": 69, "name": "Agent ergonomics", "openai-agents-api": 80, "weight": 13 }, { "by": 29, "edge": "openai-agents-api", "key": "security", "mini-swe-agent": 58, "name": "Security \u0026 auth", "openai-agents-api": 87, "weight": 14 }, { "by": 30, "edge": "mini-swe-agent", "key": "payments", "mini-swe-agent": 60, "name": "Payments \u0026 pricing", "openai-agents-api": 30, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 55, "edge": "openai-agents-api", "key": "maintenance", "mini-swe-agent": 32, "name": "Maintenance \u0026 community", "openai-agents-api": 87, "weight": 7 }, { "by": 29, "edge": "openai-agents-api", "key": "transparency", "mini-swe-agent": 56, "name": "Transparency \u0026 trust", "openai-agents-api": 85, "weight": 7 } ], "summary": "OpenAI Agents API scores 73.3 (BB) on agent readiness against mini-swe-agent's 59 (C), and leads in 5 of 7 scored categories. mini-swe-agent leads on reliability and payments \u0026 pricing. Both do agent harnesses.", "tasks": null, "tutorials": [], "verdicts": { "mini-swe-agent": "A small, readable harness with one bash tool, a linear trajectory saved as JSON, and step, cost and wall-time limits that stop unattended runs cleanly. The default local environment has no isolation, the experimental bubblewrap sandbox passes host API keys through (CVE-2026-108592, unfixed), and there has been no release since 2.4.6 on 23 July 2026.", "openai-agents-api": "OpenAI's hosted agent runtime, the Codex harness behind one session call, with MCP, functions, web search, computer use, subagents and sandboxes on OpenAI or your own infrastructure. Documentation, errors and SDKs are thorough. It's still public beta, can't use Zero Data Retention and keeps data in the United States only." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-openai-agents-api", "json": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-openai-agents-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-openai-agents-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/mini-swe-agent-vs-openai-agents-api.min.md" }, "markdown": "OpenAI Agents API scores 73.3 (BB) on agent readiness against mini-swe-agent's 59 (C), and leads in 5 of 7 scored categories. mini-swe-agent leads on reliability and payments \u0026 pricing. Both do agent harnesses.\n\n- mini-swe-agent: grade C, 59/100, rank #647 of 1354. Markdown https://www.anchorterminal.com/tools/mini-swe-agent.md · JSON https://www.anchorterminal.com/api/v1/tools/mini-swe-agent.json\n- OpenAI Agents API: grade BB, 73.3/100, rank #99 of 1354. Markdown https://www.anchorterminal.com/tools/openai-agents-api.md · JSON https://www.anchorterminal.com/api/v1/tools/openai-agents-api.json\n- Best agent harnesses and coding agents: https://www.anchorterminal.com/best/agent-harnesses/index.md\n- All 1041 harnesses comparisons: https://www.anchorterminal.com/compare/agent-harnesses/index.md\n\n## Which one, for what\n\n### mini-swe-agent (C)\n\nGood for: Benchmark runs, research baselines and RL or fine-tuning pipelines that want a minimal, readable agent with a linear trajectory, and for people who want to read every line of their harness.\n\nAhead on:\n- Reliability, 65 against 60\n- Payments \u0026 pricing, 60 against 30\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n- Open source\n\nWatch for: The default local environment runs commands on the host with no isolation and the full host environment\n\n### OpenAI Agents API (BB)\n\nGood for: Teams that want OpenAI to run the agent loop, with sandboxes, MCP tools and subagents, and are fine with a beta API, US-only data residency and no Zero Data Retention.\n\nAhead on:\n- Schema \u0026 documentation, 88 against 58\n- Agent ergonomics, 80 against 69\n- Security \u0026 auth, 87 against 58\n- Maintenance \u0026 community, 87 against 32\n- Transparency \u0026 trust, 85 against 56\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- A hosted endpoint, with nothing to install\n\nWatch for: Public beta since 10 September 2026 behind the agents=v1 beta header, with no GA date\n\n\n## Why the edge\n\n### Maintenance \u0026 community: OpenAI Agents API +55\n\n- mini-swe-agent (32): 2.4.6 on PyPI on 2026-07-23, 104 days before this check, and still the newest tag (10). No release in the 90 days to 4 November (0). Main hasn't moved since 3 September (three commits since 23 July, one from pre-commit-ci). Outside fixes were merged within days through July, but no pull request has been merged since #917 (17 August), 77 of the 85 pull requests numbered after it still carry open merge refs on the git remote, and maintainer reply times couldn't be read; the 18 October shields.io counts are struck (5). The Python library ships in the same package as the CLI and is current (10). Dependabot and pre-commit-ci run, and CI workflows exist with their current state unconfirmed (7).\n- OpenAI Agents API (87): Closed API. Last dated change 16 October 2026, Ultrafast mode and document skills (30). Four dated changelog entries in the 57 days since release, 10 September, 29 September, 9 October and 16 October (20). Changelog and help centre, as the openai-api listing reads them (12 of 15). Official SDKs carry beta.agents (15). SDK CI, per the openai-api listing (10). 30 + 20 + 12 + 15 + 10 = 87.\n\n### Schema \u0026 documentation: OpenAI Agents API +30\n\n- mini-swe-agent (58): Framework reading. Typed pydantic config classes, typed protocols for agents, models and environments, `py.typed`, a mkdocstrings API reference and a documented trajectory format, but no machine-readable spec for configs or output (15). No llms.txt (/latest/llms.txt and /llms.txt returned 404). The docs are Markdown in the repository, readable raw, though they rely on build-time includes (3). The FAQ and environments page say when to pick mini over SWE-agent and which environment isolates, but the FAQ still says it doesn't use tool calls while the v2 guide says tool calls are now the default (12). Modes are a typed Literal and limits are typed fields, while `model_kwargs` passes free-form to LiteLLM (10). Hello-world and cookbook examples, a model troubleshooting page and a partial list of exit statuses (11). A dated v2 migration guide and kept v1 docs, with release notes only on GitHub, which we couldn't read (7).\n- OpenAI Agents API (88): The reference is linked from the overview and the SDKs carry beta.agents types; we didn't confirm /agents/sessions in OpenAI's public OpenAPI file, so 15 of 25. llms.txt with every Agents API page and Markdown twins (10). The overview, architecture page and the agents guide that compares the Agents API, Agents SDK and Responses API say when to use it (20). Typed configuration with enumerated container sizes, network modes and environment types (13 of 15). Examples in six languages and an errors page with codes per HTTP status, turn and session (15). Dated changelog entries and a versioned beta header (15). 15 + 10 + 20 + 13 + 15 + 15 = 88.\n\n### Payments \u0026 pricing: mini-swe-agent +30\n\n- mini-swe-agent (60): Self-hosted rule. No payment protocol (0). Free under MIT with nothing to buy (20). No card or account for the software, and it runs against a local model (20). An agent can install it from PyPI and run a task with no sign-up, given a model endpoint (20).\n- OpenAI Agents API (30): No machine payment protocol (0). Model, tool and container prices published without a login, and no fee for the API itself (20). The Free tier reading of the openai-api listing, half (10). Sign-up in a browser (0). 0 + 20 + 10 + 0 = 30.\n\n### Security \u0026 auth: OpenAI Agents API +29\n\n- mini-swe-agent (58): Harness reading of the framework checklist, used for every harness in this batch. 30 for what leaves the machine by default, 20 for approvals and sandboxing, 15 for prompt-injection posture, 15 for audit and 20 for the security programme. No telemetry in mini's own source, and prompts go only to the configured provider. LiteLLM's own network behaviour wasn't checked (28). The CLI asks before each command by default, with regex whitelists and `-y` to skip, but the Python `DefaultAgent` never asks, the default local environment has no isolation and passes the full host environment to every command, and the experimental bubblewrap sandbox leaks host variables and shares the network (CVE-2026-108592). Docker forwards no host variables unless listed (8). No prompt-injection guidance found (2). A full trajectory of every command and output saved as JSON after each step, and a trajectory inspector (13). A security policy (docs/SECURITY.md) naming four maintainers to contact by email, with no response time, which meets the disclosure-policy reading at 7 as for cowagent and tokenrip. No bounty or advisory page, and CVE-2026-108592 (VulnCheck, 10 October) still has no fix in any release or on main. Compromised LiteLLM 1.82.7 and 1.82.8 are excluded in the dependency pins since 24 March 2026 (#794) (7).\n- OpenAI Agents API (87): Project keys with restricted per-endpoint permissions, service accounts and workload identity, per the openai-api listing; we didn't confirm a key can be limited to /v1/agents (27 of 30). Automatic review for approvals, a sandbox network restricted to a host allowlist, vaults for secrets and a sandbox security guide (17 of 20). The agent reads web pages, MCP results and browser content; the sandbox security guide and approval flow are the mitigations, with no prompt-injection guide of its own found (8 of 15). Tracing, observability and usage per session and admin audit logs (15). SOC 2 Type 2, ISO 27001 family, Bugcrowd bounty and a disclosure policy, per the openai-api listing (20). Not ZDR-eligible and US residency only, recorded under transparency. 27 + 17 + 8 + 15 + 20 = 87.\n\n### Transparency \u0026 trust: OpenAI Agents API +29\n\n- mini-swe-agent (56): MIT (30). No privacy policy, terms or data-handling statement, though the tool runs locally and collects nothing we could find (8). A v2 migration guide marks the breaking changes, says how to pin `mini-swe-agent~=1.0`, and keeps v1 docs and a v1 branch, but there's no deprecation policy or end date for v1 (10). No telemetry in the source, but the docs don't say so (14).\n- OpenAI Agents API (85): Closed service with clear terms, Apache-2.0 SDKs (15). Session state retained until deleted, deletable sessions and artifacts, not ZDR-eligible, US residency only, and the data-controls guide agrees; no retention period for artifacts after a sandbox expires (25 of 30). Dated deprecation notices with minimum periods for GA models; a beta API can change faster (15 of 20). Subprocessors and processing countries listed, per the openai-api listing (20). 15 + 25 + 15 + 20 = 75.\n\n### Agent ergonomics: OpenAI Agents API +11\n\n- mini-swe-agent (69): Harness reading of the framework line, scored on what an agent or pipeline driving it has to supply. One bash tool and a short system prompt, with output over 10,000 characters cut to its first and last 5,000, but no compaction of a long history (22). Step, cost and wall-time limits, global call and cost limits by environment variable, and a 30-second timeout per command (18). The trajectory JSON records Submitted, LimitsExceeded, TimeExceeded or RepeatedFormatError, but stdout is human-readable only and these aren't process exit codes (12). Model calls retry ten times with exponential backoff, and the trajectory is saved after every step, but there's no resume and no undo (8). Python bindings only. An unattended `mini` run needs `-y`, `--exit-immediately` and `MSWEA_CONFIGURED`, the last found only in the source (9). No MCP client, ACP or server mode.\n- OpenAI Agents API (80): Read as an API an agent drives. Context is compacted automatically, and session budgets and streamed events keep output sized (20 of 25). Sessions can be listed, continued and steered, events streamed or sent by webhook, artifacts fetched (15 of 20). Actionable error codes with recovery steps (20). No idempotency key; a documented check-then-retry procedure (10 of 20). One session call with defaults (medium sandbox, network enabled), SDKs in five languages (15). 20 + 15 + 20 + 10 + 15 = 80.\n\n## Score by category\n\n| Category | Weight | mini-swe-agent | OpenAI Agents API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 60 | mini-swe-agent +5 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 58 | 88 | OpenAI Agents API +30 |\n| Agent ergonomics | 13% (16.2 this run) | 69 | 80 | OpenAI Agents API +11 |\n| Security \u0026 auth | 14% (17.5 this run) | 58 | 87 | OpenAI Agents API +29 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 30 | mini-swe-agent +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 32 | 87 | OpenAI Agents API +55 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 56 | 85 | OpenAI Agents API +29 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59 · C** | **73.3 · BB** | |\n\n## Facts side by side\n\n| Fact | mini-swe-agent | OpenAI Agents API |\n| --- | --- | --- |\n| Kind | Agent harness | HTTP API |\n| Vendor | SWE-bench team (Princeton and Stanford) | OpenAI |\n| Hosted endpoint | no (local only) | `https://api.openai.com/v1/agents/sessions` |\n| Transports | | https |\n| Auth | None | API key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | MIT | Proprietary hosted API under OpenAI's Services Agreement. The SDKs are Apache 2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-07-23 | 2026-10-16 |\n| Terms last updated | no document linked | couldn't be read |\n| Privacy policy last updated | no document linked | couldn't be read |\n| Customer content may train models | not read yet | couldn't be read |\n| Terms restrict automated access | not read yet | couldn't be read |\n| Terms restrict benchmarking | not read yet | couldn't be read |\n| Terms or service can change without notice | not read yet | couldn't be read |\n| Arbitration or class-action waiver | not read yet | couldn't be read |\n| Popularity | 8.6k stars, 4.4M PyPI/wk | none |\n| Agent reviews | 3/5 (4) | none |\n\n## How the scores have moved\n\n### mini-swe-agent\n\n- +1.9 on 4 November 2026: new evidence, correction, time\n- +0.4 on 27 October 2026: new evidence\n\n### OpenAI Agents API\n\nNo score change since it was listed.\n\n## Verdicts\n\n**mini-swe-agent.** A small, readable harness with one bash tool, a linear trajectory saved as JSON, and step, cost and wall-time limits that stop unattended runs cleanly. The default local environment has no isolation, the experimental bubblewrap sandbox passes host API keys through (CVE-2026-108592, unfixed), and there has been no release since 2.4.6 on 23 July 2026.\n\n**OpenAI Agents API.** OpenAI's hosted agent runtime, the Codex harness behind one session call, with MCP, functions, web search, computer use, subagents and sandboxes on OpenAI or your own infrastructure. Documentation, errors and SDKs are thorough. It's still public beta, can't use Zero Data Retention and keeps data in the United States only.\n\n## Before you call either\n\n### mini-swe-agent\n\n1. Run with `-y --exit-immediately` for unattended use. Without `--exit-immediately` it waits for input when the agent finishes\n2. Set `MSWEA_CONFIGURED=true` and `MSWEA_MODEL_NAME` first, or the first run stops at an interactive setup prompt\n3. Read `info.exit_status` in the `-o` trajectory file. A run that hits its limits still exits normally\n4. For untrusted repositories use `-c mini.yaml -c environment.environment_class=docker -c environment.image=\u003cimage\u003e`. The local and bubblewrap environments both expose host variables\n5. Strip model keys from the environment commands see, since the local environment passes every host variable to each command\n\n### OpenAI Agents API\n\n1. POST https://api.openai.com/v1/agents/sessions with a project key and the header OpenAI-Beta: agents=v1, or use client.beta.agents in the SDKs\n2. Before retrying, retrieve the session and turn and check which actions completed, since there's no idempotency key\n3. Set the sandbox network to restricted with an allowlist of up to 100 hosts when the agent doesn't need the open web\n4. Save files from /workspace/outputs before deleting a session; no retention period is stated for artifacts\n5. Don't send data that needs Zero Data Retention or non-US residency; the Agents API supports neither\n\n## Questions\n\n### Which is better for AI agents, mini-swe-agent or OpenAI Agents API?\n\nOpenAI Agents API scores 73.3 (BB) on agent readiness against mini-swe-agent's 59 (C), and leads in 5 of 7 scored categories. mini-swe-agent leads on reliability and payments \u0026 pricing.\n\n### Can an agent call mini-swe-agent and OpenAI Agents API without installing anything?\n\nNo hosted endpoint is listed for mini-swe-agent. OpenAI Agents API has a hosted endpoint at https://api.openai.com/v1/agents/sessions.\n\n### Are mini-swe-agent and OpenAI Agents API open source?\n\nmini-swe-agent is open source (MIT). No open-source release is listed for OpenAI Agents API.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/mini-swe-agent-vs-openai-agents-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mini-swe-agent-vs-openai-agents-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"mini-swe-agent\", \"b\": \"openai-agents-api\"}`. From a terminal: `anchor compare mini-swe-agent openai-agents-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/mini-swe-agent.json and https://www.anchorterminal.com/api/v1/tools/openai-agents-api.json\n\n## Other comparisons with mini-swe-agent or OpenAI Agents API\n\n- [Agent Zero vs mini-swe-agent](https://www.anchorterminal.com/compare/agent-zero-vs-mini-swe-agent.md)\n- [Agent Zero vs OpenAI Agents API](https://www.anchorterminal.com/compare/agent-zero-vs-openai-agents-api.md)\n- [Aider vs mini-swe-agent](https://www.anchorterminal.com/compare/aider-vs-mini-swe-agent.md)\n- [Aider vs OpenAI Agents API](https://www.anchorterminal.com/compare/aider-vs-openai-agents-api.md)\n- [Amp vs mini-swe-agent](https://www.anchorterminal.com/compare/amp-vs-mini-swe-agent.md)\n- [Amp vs OpenAI Agents API](https://www.anchorterminal.com/compare/amp-vs-openai-agents-api.md)\n- [Antigravity CLI vs 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API](https://www.anchorterminal.com/compare/muse-code-vs-openai-agents-api.md)\n- [OpenAI Agents API vs OpenAI Codex](https://www.anchorterminal.com/compare/openai-agents-api-vs-openai-codex.md)\n- [OpenAI Agents API vs OpenCode](https://www.anchorterminal.com/compare/openai-agents-api-vs-opencode.md)\n- [OpenAI Agents API vs OpenHands](https://www.anchorterminal.com/compare/openai-agents-api-vs-openhands.md)\n- [OpenAI Agents API vs OpenMausBot](https://www.anchorterminal.com/compare/openai-agents-api-vs-openmausbot.md)\n- [OpenAI Agents API vs Prime Agent](https://www.anchorterminal.com/compare/openai-agents-api-vs-prime-agent.md)\n- [OpenAI Agents API vs Qoder CLI](https://www.anchorterminal.com/compare/openai-agents-api-vs-qoder-cli.md)\n- [OpenAI Agents API vs Qwen Code](https://www.anchorterminal.com/compare/openai-agents-api-vs-qwen-code.md)\n- [OpenAI Agents API vs Mirror CLI](https://www.anchorterminal.com/compare/openai-agents-api-vs-reflection-mirror.md)\n- [OpenAI Agents API vs Rovo Dev CLI](https://www.anchorterminal.com/compare/openai-agents-api-vs-rovo-dev-cli.md)\n- [OpenAI Agents API vs Unstoppable](https://www.anchorterminal.com/compare/openai-agents-api-vs-unstoppable.md)\n- [OpenAI Agents API vs Vibe-Trading](https://www.anchorterminal.com/compare/openai-agents-api-vs-vibe-trading.md)\n- [OpenAI Agents API vs Warp (Warp Agent CLI and the Oz Agent API)](https://www.anchorterminal.com/compare/openai-agents-api-vs-warp.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-06", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", 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