Reviews

Pros

• Per-model credit factors are public in the docs without a login
• Failed Qoder model requests don't use credits
• --max-turns and --max-output-tokens bound headless runs

Cons

• Credit Packs expire after one month and aren't refundable
• Credits per request are published only as medians
• Credit factors changed on 21 September 2026, Ultimate from 1.6x to 2x
• qoder.com/pricing is disallowed by robots.txt and wasn't read

Pros

• Every release dated in the release notes
• Two weeks' notice before the Lite tier removal
• Dated notice for the 21 September credit factor change

Cons

• Auto-upgrade on by default
• Removals shipped in patch versions without a label
• CLI reference still names the removed lite model
• SDK release notes twelve versions behind npm

Pros

• Trusted folders gate project config, hooks and MCP servers, and -p needs --trust
• Read-only plan agent and bash allow and deny lists
• Valid security.txt, a HackerOne programme and dated advisories with CVEs
• Opt-in OpenTelemetry with a strict redaction mode

Cons

• Default agent auto-approves file edits, with no host sandbox
• Six High shell-permission bypasses fixed only on 12 September 2026
• Telemetry experiments can switch the default agent to smart-approve
• The offline guide names an enable_auto_update key the source doesn't define, so update checks stay on

Pros

• Turn, token, price and wall-time budgets for headless runs
• Exit codes 0 to 4 with the outcome named in export.json
• SIGTERM stops a run so it can be resumed

Cons

• All four budgets are off unless set
• Retry count and backoff not stated
• CI pass state and open issues unchecked
• Hosted runs depend on Mistral plan limits and pay-as-you-go settings

Pros

• Exit codes 0 to 4 mapped to named outcomes in export.json
• llms.txt with a Markdown twin for every CLI page
• Configuration reference gives each key's type and default, and the config is validated on load
• --agent-socket JSON-RPC methods documented with typed params and results

Cons

• The offline guide and configuration reference name enable_auto_update, a key the source doesn't read
• The safety page gives the wrong default agent for -p
• No published schema file for the config or the streaming events
• TODO notes for developers left in the API keys and offline pages

Pros

• Dated Keep a Changelog file with Removed sections
• 20 PyPI releases in 90 days, 2.26.1 on 9 October 2026
• The local model removal warns and falls back
• Hooks marked stable since 2.21.0

Cons

• Hooks rename shipped in minor 2.21.0
• Patches 2.11.1 and 2.26.1 changed a default and removed a feature
• Docs name an update key the code doesn't read
• The agent socket may change without notice

Pros

• No telemetry in the source, and prompts go only to the configured provider
• The mini CLI confirms each command by default
• The Docker environment forwards no host variables unless listed
• Full trajectory saved as JSON after every step

Cons

• Default local environment has no isolation and passes the full host environment
• CVE-2026-108592 unfixed in 2.4.6
• The Python DefaultAgent never asks before a command
• No prompt-injection guidance, and the security page gives no response time

Pros

• $3 cost limit per run by default, plus step and wall-time limits
• 30-second timeout per command, with the process group killed
• Ten retries with exponential backoff on model calls
• Trajectory saved after every step

Cons

• Limit and timeout outcomes aren't process exit codes
• Waits for input without --exit-immediately
• MSWEA_CONFIGURED is found only in the source
• No resume and no undo

Pros

• One bash tool and a short system prompt
• Long command output cut to its first and last 5,000 characters
• Typed pydantic config classes, py.typed and a documented trajectory format
• Exit statuses such as LimitsExceeded and TimeExceeded recorded in the trajectory

Cons

• The FAQ says it doesn't use tool calls, while v2 makes them the default
• MSWEA_CONFIGURED, needed to skip the first-run prompt, is in the source only
• No llms.txt, and the docs rely on build-time includes
• Run outcomes aren't process exit codes, and the list of exit statuses is partial

Pros

• v2 migration guide with a kept v1 branch and docs
• Step, cost and wall-time limits for long runs
• Trajectory saved after every step

Cons

• One release in 90 days, the last on 23 July 2026
• CVE-2026-108592 has no fixing release
• No changelog file, and tags carry only a version bump
• No resume after an interrupted run

Pros

• OAuth tokens stored in 0600 files, and shell keys read only when named
• Workspace trust gates project config since 2.1.0
• The MCP page warns about untrusted servers and project mcp.json entries

Cons

• kimi -p approves everything with the dangerous-command guard off
• No sandbox documented, and hooks fail open
• Telemetry on by default with no list of what it sends
• No security.txt, and SECURITY.md gives no response time

Pros

• Retries on 429, 5xx, timeouts and connection errors, up to 10 a step
• No retry on an exhausted quota
• --continue, --session, fork and undo
• Coded error envelopes on the server API and JSON-RPC errors on ACP

Cons

• Steps per turn unlimited by default
• No wall-time or cost limit for the main turn
• Print-mode exit codes documented only for goal runs
• Auto-update on by default, and 2.2.0 broke executor = "kaos" configs in a minor release

Pros

• llms.txt and a Markdown version of every docs page
• Config keys documented with type, default and enums
• OpenAPI and AsyncAPI documents generated from the server's runtime validation schemas
• ACP methods and capabilities tabled, with ACP error codes

Cons

• Print-mode exit codes are documented only for goal runs
• The OpenAPI and AsyncAPI documents are reachable only from a running server behind auth, and the API is experimental

Pros

• 32 npm releases in 90 days, 2.2.0 on 14 October 2026
• Deprecated config keys listed with their replacing version
• kimi server prints a deprecation notice
• kimi migrate and a guide for the archived Python CLI

Cons

• 2.2.0 broke executor = "kaos" configs in a minor release
• Major version bump without a matching breaking change
• Auto-update on by default
• No date for when archived Python installs stop working

Pros

• Allowlist checks each part of chained, nested and multi-line commands
• Interactive runs keep an untrusted project's MCP servers and hooks unloaded
• Coordinated disclosure policy, a security.txt contact and CVEs through NVD

Cons

• Non-interactive runs load project MCP servers and hooks without asking
• Sandbox EAP-only, off by default, absent on Windows, network open
• Junie API keys are long-lived with no scopes found
• The CLI's default for anonymous statistics isn't stated

Pros

• CLI reference lists every flag with examples
• Documented formats for the allowlist, config.json, custom model profiles and hook payloads
• Nine StopFailure categories named in the hooks page
• Dated docs pages and a dated release list

Cons

• No schema for json or json-stream output, and no exit codes
• The headless page doesn't cover what happens when an action needs approval
• llms.txt doesn't index the docs, and pages returned HTML when Markdown was requested
• Effort values differ between the CLI reference and the model page

Pros

• Junie Lite is free and needs no card
• BYOK use is billed by the provider with no JetBrains markup
• One credit is US$1, and top-ups stay valid for 12 months

Cons

• Per-model credit rates were not found
• No turn or spend cap is documented for headless runs
• Junie Lite's quota isn't published

Pros

• Every build dated on What's New
• --use-version and --skip-update-check pin a build
• Retired flags kept as deprecated compatibility options
• Separate release, eap, nightly and experimental channels

Cons

• Self-update on start by default
• One-line notes with no breaking changes called out
• npm five weeks behind the release feed
• GA and EAP status contradict each other

Pros

• Each task runs in a short-lived VM, away from the caller's machine
• Exposed keys disabled automatically, at most three at a time
• The GitHub app can be limited to chosen repositories
• Every plan, bash command and patch logged as activities

Cons

• Keys carry no scopes, and there's no read-only key
• Plans auto-approved on API sessions unless requirePlanApproval is set
• Task VMs have internet access, and the FAQ puts the burden on the user
• The Jules privacy notice was unreadable, so retention is unknown

Pros

• Public discovery document with 13 methods, 33 typed schemas, enums and required fields
• MCP tool descriptions say when to use each tool
• llms.txt with a Markdown twin of every docs page
• curl examples on every endpoint page and a documented error table

Cons

• Two MCP tool descriptions name jules_sync and jules_select, which don't exist
• No readOnlyHint or destructiveHint annotations, and create_session defaults to autoPr true
• Field tables on the reference pages render empty
• Archive and unarchive appear only in the discovery document

Pros

• Public discovery document with a dated revision
• Alpha notice promises one stable and one experimental version
• Dated public changelog

Cons

• No changelog entry or package release since 9 March 2026
• Archive and unarchive added without a dated note
• API alpha since 3 October 2025
• No status page found

Pros

• No card step found for the free plan of 15 tasks a day and 3 concurrent
• After setup, only prompt is required to create a session
• A session without a source runs repoless in a fresh cloud VM
• Four ways in once a key exists, the REST API, TypeScript SDK, MCP server and CLI

Cons

• Keys are created only by a person in the web app, at most three, and carry no scopes
• The Jules Tools CLI documents Google browser sign-in only, with no API key option
• Paid plans are for personal @gmail.com accounts, and Jules is limited to people 18 and over
• jules.google.com answered that Jules is not available in our region, so the privacy notice went unread

Pros

• An unanswered approval is denied in headless and ACP runs
• Writes confined to the workspace by OS mechanisms on three platforms
• No MCP server enabled by default
• Approval decisions recorded in local JSONL session logs

Cons

• Session-log upload to DeepSeek on by default, disclosed only in reference pages
• Reads and network unconfined, and web_fetch needs no approval
• Eight NVD records with no patched version, six saying the vendor did not respond
• No SECURITY.md, security.txt or security audit

Pros

• --dump-config-schema emits JSON Schema 2020-12 for the composed configuration
• Documented NDJSON event types (session, status, text, thinking, tool_call, tool_result, final, error)
• llms.txt and raw Markdown for every docs page
• Package READMEs say when to use and avoid each part, with known limitations

Cons

• A failed in-turn run can still end with a final event
• Exit codes are 0 and 1 only
• No changelog, and the reference marks the schema output as pre-stable
• Session-log upload and telemetry are described in reference pages, not in the README or SAFETY.md

Pros

• 36 npm versions between 10 August and 17 October 2026
• Separate alpha, next and latest channels
• The Python SDK ships with each release

Cons

• No changelog or breaking-change notes found
• npm latest is behind the version DeepSeek's changelog asks for
• README warns of breaking changes without listing them
• External pull requests not accepted

Pros

• No account, card or sign-up for the harness, which is free under MIT
• A headless run is one command with DEEPSEEK_API_KEY in the environment
• The Python SDK installs from PyPI with a bundled runtime and needs no system Node.js
• Custom OpenAI or Anthropic-compatible endpoints, including self-hosted servers, can replace DeepSeek's API

Cons

• DeepSeek's API is a separate purchase, and the steps to get its key are unchecked here
• npx @deepseek-ai/dsh installs latest 0.2.0-rc.2, while DeepSeek's changelog asks for 0.2.1-rc.1 or later
• Session-log upload to DeepSeek is on by default and documented in reference pages, not the README or SAFETY.md
• Whether the Web UI or desktop app shows the upload at first run is unchecked

Pros

• Releases cosign-signed, with CodeQL, Grype and govulncheck in CI
• PreToolUse hooks can block or rewrite tool calls
• Provider keys stay local, and a local model needs no account
• No advisories for Crush in OSV or NVD

Cons

• crush run approves every permission request, and the README doesn't say so
• No sandbox, only a fixed list of refused commands
• A project's .crushrc and crush.json substitutions execute at startup
• Usage metrics on by default, aliased to the Hyper account after login

Pros

• --session and --continue resume a run
• Session commands return JSON with --json
• MCP servers take per-server timeouts

Cons

• No turn, time or cost limit on crush run
• No documented exit codes and no JSON error record
• Provider retry and 429 behaviour unchecked
• CI state and open issues unchecked after GitHub answered 403

Pros

• Config JSON Schema with enums and defaults, also printed by crush schema
• crush session commands take --json
• Many examples for providers, MCP, hooks and local models, and a hooks guide written for humans and agents

Cons

• crush run output is plain text with no JSON format
• No reference for error messages or exit codes
• No llms.txt, and the OpenAPI document is generated only by a running crush server
• The README names crush serve where the source defines crush server, and omits that crush run approves everything

Pros

• 20 npm releases in 90 days, the latest on 9 October 2026
• Deprecated JSON config still loads alongside crushrc
• The update check notifies and installs nothing
• npm, Homebrew, Winget, Scoop, apt, yum and NUR builds track releases

Cons

• Pre-1.0 with no stability statement
• No changelog file, only notes generated from commits
• No removal date for the deprecated JSON config

Pros

• Most restrictive rule wins across policy sources
• Webhook and script policies let a security team decide each call
• Writes to sensitive paths need approval since 0.34.0
• SOC 2 Type II named, and no CVE in NVD

Cons

• Default for unmatched tools undocumented, and the MCP page says tools run automatically
• Workspace uploaded for indexing by default, in print mode too
• Service account tokens never expire until deleted
• 1.x renames tools, so deny rules using some legacy names stop applying

Pros

• auggie tools schemas prints tool definitions and input schemas
• llms.txt with a Markdown twin of every page, plus a docs MCP server
• Permission types, tool names, event types and log levels are enumerated, and a malformed rule is dropped with a warning
• Hook exit codes are documented

Cons

• No schema for --output-format json or settings.json
• No exit codes or error format for print mode
• The default for tools no permission rule matches isn't defined
• 1.x tool renames leave some legacy names unmatched by permission rules

Pros

• Token rates, the 40 per cent fee and plan prices are public without a login
• --max-turns and --show-credits in print mode bound and report usage
• Top-ups last 12 months

Cons

• A 40 per cent service fee on every model token
• No free tier on the pricing page
• Per-user budgets exist only on Enterprise
• Whether failed runs are charged was not found in the reviewed documentation

Pros

• 1.x migration guide lists breaking changes
• Print mode doesn't auto-update
• Dated CLI entries on the website changelog

Cons

• Stable line unchanged since 21 August 2026
• No date for 1.x becoming latest
• 1.x tool renames can leave deny rules unmatched
• Licence and terms not yet updated after the acquisition

Pros

• Hosted MCP uses OAuth 2.1 with PKCE S256, dynamic client registration and revocation, and stores no key in the client
• No MCP tool deletes, and write takes dry_run and an idempotency key
• SECURITY.md since 14 September 2026 takes reports through GitHub private vulnerability reporting

Cons

• No read-only mode, per-project scope or OAuth scopes, and the docs leave write approval to the client
• Service accounts and view-only users are listed under Enterprise, so a Free or Pro key carries full rights, deletes included
• Trace content comes back with nothing marking it untrusted, and no audit log was found
• Unchecked whether the Comet API key also authorises Comet's MLOps APIs, and the advisories page wasn't read

Pros

• Five MCP tools, with when-to-use guidance in the docstrings
• Write payload schemas fetched on demand through schema
• Stable error codes with a corrected example on validation failure
• llms.txt and a Markdown twin of every docs page

Cons

• REST descriptions mostly repeat the operation summary
• REST filters and sorting are free-form strings
• Only one OpenAPI operation carries an example, and 7 of 316 declare 429
• MCP write.data is an open object, checked against its schema only at call time

Pros

• Pro rates published without a login, $19 a month and $5 per 100,000 spans
• Free Cloud covers 25,000 spans a month with 60 days of retention
• Five MCP tools with write schemas fetched on demand keep the context cost small

Cons

• No x402, MPP or L402, and paid plans start from a browser sign-up at comet.com
• Not found whether rejected requests count as spans or whether Free Cloud needs a card
• Service accounts and view-only users are listed under Enterprise, which is custom-priced

Pros

• 104 release tags from 20 July to 16 October 2026 and a weekly dated changelog
• The npm MCP server shutdown is dated 15 November 2026 with a migration guide to uvx opik-mcp
• Opik 2.0 shipped with an upgrade guide and self-hosted migration jobs
• Versioned /v1 paths and a separate self-hosted changelog of breaking changes

Cons

• No general deprecation policy found
• Status history holds one maintenance from 2 June 2024, with no component for the MCP server or ingestion
• CI pass state across 86 workflow files and issue reply times are unchecked
• Local npx opik-mcp installs stop serving requests on 15 November 2026

Pros

• The Codex bridge binds 127.0.0.1 by default, with a generated key stored at mode 0600
• No telemetry found in the Harness² source
• Each editor call's prompt, response, model and cost are saved to an audit folder
• The bypass flags and open network access are stated in the README and setup guide

Cons

• Executors inherit the whole shell environment, and the editor channel drops only five Anthropic variables
• The docs report a Codex rollout that fetched its rubric unprompted, and give no guidance on instructions inside task documents
• No SECURITY.md or security.txt, and the README says it is outside Google's vulnerability rewards programme
• No .gitignore keeps a filled-in .env out of commits, and OpenCode telemetry for LAB and JobBench runs is unchecked

Pros

• --help and a worked example for every command
• ConfigError messages name the remedy
• Fixed choices for --bench, --split and --substrate, and typed numbers
• harness2-check tests configuration without a model call

Cons

• No API reference, llms.txt or changelog
• The quick start copies .env.example, which the repository doesn't contain
• Model IDs are free strings checked only for a slash
• No documented path to tasks outside JobBench, LAB and WorkBuddy-Bench

Pros

• Dependencies pinned by version and upstream checkouts by commit, with OpenCode at v1.14.18 and Codex CLI at 0.144.6
• Rerunning a command resumes it, and saved configuration refuses an incompatible resume
• Failed grades stay unscored rather than counted as zero

Cons

• No tags, GitHub releases, changelog or deprecation notices for the 0.1.0 research release
• No CI workflow, and five unit tests over the deterministic demo
• 42 pull requests and 6 issues open on 18 October 2026, with no outside change on main
• The README says it is not an officially supported Google product

Pros

• No Harness² account, key or card
• harness2-demo runs with no credentials
• harness2-check tests credentials and configuration without a model call
• Configuration errors name the remedy

Cons

• A person must set up a Vertex AI project and a gcloud sign-in or service account key
• The quick start copies .env.example, which the repository doesn't contain
• Installs from a source checkout only, and harness2 isn't on PyPI
• Whether a wheel build works is unchecked

Pros

• Deploy-only project credentials expire after 1 to 90 days and are revocable
• Human tokens kept in the OS keychain, and login fails closed without one
• Destructive database commands ask first and stop non-interactively without --yes

Cons

• Direct deploys act with the full rights of the owner's Cloudflare token
• No untrusted-content guidance for void project logs and requests output
• No security.txt and no npm provenance attestations
• No terms or privacy policy on void.cloud

Pros

• Docs and two agent skills ship inside the npm package, matched to the installed version
• The CLI reference warns that void db reset drops deployed tables when .env points at production
• Installer and deploy errors name the fix and link the docs page, such as Analytics Engine code 10089

Cons

• --json is documented only for platform administration and void info, not for deploy or project commands
• No llms.txt (HTTP 404 on void.cloud) and no catalogue of error codes
• No changelog or release notes were found, so breaking changes are not called out

Pros

• Release tags must be exact semantic versions under a policy script
• Deploys save a D1 restore point and print the undo command
• Docs for the installed version ship inside the npm package

Cons

• No changelog or release notes found
• Depends on a prerelease of Cloudflare's cf CLI
• Requires Node.js 24.21.0 or later

Pros

• npm install -D void and npx void init need no account
• Project-scoped deploy credentials reach only deploy endpoints and can be revoked
• Native apps run on Workers Free
• Destructive database commands stop without --yes in a non-interactive shell

Cons

• Deploying needs a person-created Cloudflare account and a login or token
• A direct Cloudflare deploy runs with whatever rights the owner's token carries
• No public sign-up for VoidZero's own Void Cloud deployment was found
• Requires Node.js 24.21.0 or later

Pros

• Keys take project scope, expiry and budget, and are revocable by leak report
• OIDC tokens replace long-lived keys on Vercel deployments
• Prompt and response content is not kept by the gateway

Cons

• No per-model or read-only key scope
• No-training and ZDR are opt-in per request, and ZDR is unavailable on Hobby
• Contractual no-training promise covers Enterprise only
• April 2026 incident decrypted some customers' environment variables

Pros

• Automatic failover across providers, plus configurable model fallbacks
• 429 and 402 are distinct, with backoff code in the docs
• Status history of 25 incidents names none for AI Gateway

Cons

• No rate-limit numbers, and the paid tier has no gateway limit
• No SLA covers the API
• Token Pass requests do not fail over, and a spent $80 credit returns 403

Pros

• No markup or platform fee, including BYOK
• Per-token prices for every model are public in the keyless model list
• Budgets per team, project, key or member, with alerts at 50, 75 and 100 per cent
• Per-request ZDR is free, and team-wide ZDR is $0.10 per 1,000 requests

Cons

• The monthly free credit amount is not stated and needs a payment method
• A budget is a soft cap checked at the start of a request, and BYOK spend does not count
• A failed BYOK request falls back to Vercel credentials and bills credits
• Only team-wide ZDR says failed requests are not charged

Pros

• GET /v1/models needs no key and lists prices, context windows and flags for 474 models
• Later keys can be created with POST /v1/api-keys once an account exists
• Keys can be limited to one project and given an expiry and a budget
• A spent budget answers 402, apart from a 429 rate limit

Cons

• The getting-started page and FAQ say the team must add a payment method before using the free credit
• The first key still needs a person with a browser
• Token Pass needs a Pro plan and a dashboard subscription
• No x402, MPP or L402

Pros

• Read-only and inference key scopes
• Monthly spend cap on inference keys
• No key can create keys, buy credit or change settings
• Request content discarded after the answer, per the docs

Cons

• No warning that hostile context can steer an answer
• No security.txt, disclosure policy or certification found
• Terms and privacy policy unchecked behind a bot check
• No key expiry found, rotation is by replacement

Pros

• retryable on every error
• Idempotent replays for 24 hours without a second charge
• Fallback can be set to none

Cons

• No status page, and status.sqwish.ai doesn't resolve
• Tier limits are not published as numbers
• No SLA, and the terms say no uptime is promised unless agreed in writing

Pros

• Typed OpenAPI 3.1 with llms.txt on two hosts and Markdown twins
• Every error carries retryable and request_id
• Idempotency-Key replay rules spelled out

Cons

• MCP tool definitions and annotations unread
• No API or model changelog, and the OpenAPI version is 0.1.0
• Rate-limit numbers readable only from an account

Pros

• Prices published without a login, from $0.02 per million input tokens
• Failed calls and idempotent replays aren't billed
• Inference keys can carry a monthly spend cap
• Training is charged only if the job succeeds, at least $2.50 a job

Cons

• Terms, refund and credit expiry rules weren't read
• Rate limits depend on a tier and no numbers are published
• New accounts may wait on a waitlist, and only the console buys credit

Pros

• Every tool carries readOnlyHint and destructiveHint
• OAuth with PKCE or device flow, revocable, refused in a query string or cookie
• Spend requests need shopper approval and issue a single-use card

Cons

• Confirmation before complete_checkout is guidance, not enforced
• One scope covers every signed-in tool
• Checkout IDs and continue_url carry an access key
• Server returns next[] suggestions addressed to the agent

Pros

• Every tool carries readOnlyHint and destructiveHint, and writes take an idempotency key
• Tool errors carry a code, retry_after and the upstream status, and checkout messages carry a severity saying who can fix them
• The errors guide says which calls can be repeated and that complete_checkout never can
• A skill is served at https://mcp.shop.com/skill.md, and every shop.dev page has a Markdown twin

Cons

• Definitions total 65,541 bytes, and update_checkout, search_catalog and create_checkout are each over 9 KB
• shop.dev's tool reference calls the card-approval tools create_approval to complete_approval, while the server serves create_spend_request and its siblings
• Cart and checkout updates replace the whole document, so omitted fields and lines are deleted
• No llms.txt (404)

Pros

• Catalogue search, carts and checkout need no account or key
• Writes take an idempotency key, and the errors guide says complete_checkout is never resent
• Device flow lets code without a browser get the shopper's sign-in

Cons

• No webhooks at launch, and no cancel for carts or checkouts
• shop.dev calls the card-approval tools create_approval and siblings, while the server serves create_spend_request
• Cart and checkout updates replace the whole document, so omitted lines are deleted
• robots.txt bars payment without a final human review, while the CLI README lets an agent buy within a budget without asking

Pros

• Search, carts and checkout need no key, account or card
• Shopper sign-in supports device flow, PKCE and token revocation
• Shop Pay spending is capped by a budget the shopper delegates
• A spend request returns a single-use card only after the shopper approves it in Shop

Cons

• Shopper sign-in is still a browser or device-code step for account and order tools
• shop.dev names the five spend tools create_approval and so on, while the server serves create_spend_request
• The shop.com robots.txt bars flows that pay without a final human review, while the CLI README describes unattended purchases within a budget
• Only MCP 2026-07-28 is accepted

Pros

• Agent sees only mock tokens, and keys are scoped to chosen cards and logins
• Automatic key revocation after three cross-account token attempts
• Approval for first fills on new sites and purchases above a set amount

Cons

• Hosted proxy holds the card number in memory, contrary to the home page
• Only the first card gets a starter agent card with caps
• Agent Vault's own terms are not published
• Activity recording is best effort and failed events are dropped

Pros

• Free plan needs no card
• Plan prices and payment quotas are public
• The merchant charges the holder's own card, and Agent Vault moves no money itself

Cons

• No per-unit price, only plan quotas
• A fill that fails after the number reaches the page can still count as a payment
• Enterprise is priced on request
• A person must sign in and add a card, so an agent cannot get access without them

Pros

• HTTP API versioned in the path
• Retired endpoints answer 410 naming the replacement
• Error reference states per code whether a retry is safe

Cons

• Tarballs changed without a version bump
• Changelog link leads to a repository that is not public
• No status page, SLA or deprecation policy
• SDK installs from a URL that npm 12 accepts only with --allow-remote=all

Pros

• Free is $0 and needs no card for Agent Vault itself
• API keys are limited to chosen cards and logins, with signups off by default
• Agent cards cap spend per transaction, day, week and rolling 30 days
• Purchases above a set amount wait for the holder's approval

Cons

• The docs say an agent cannot get access without that person
• Only the first card gets a starter agent card, so later cards have no caps until added
• No x402, MPP or L402, and the tool moves no money itself
• The hosted MCP server's live tool list was not read because that needs an account

Pros

• Manual approval by default for shell commands, writes and MCP tools
• Provider keys kept out of the environment of commands the agent runs
• A cloned repository can't add MCP servers, and project extensions ask with Disable preselected

Cons

• No sandbox by default, and extensions and local MCP servers run on the host
• Auto approval mode is saved globally across directories
• Debug logs contain the API key, per the docs
• Analytics on by default with an install ID and conversation IDs

Pros

• llms.txt with a Markdown copy of every page, and examples on every page
• enabledTools limits each MCP server's tools, and /context breaks down context use by source
• The agent protocol is published as protobuf definitions in protocols/

Cons

• No JSON Schema for config.json or the MCP definition files
• exec returns 0 whenever it prints an answer, and approval calls fail in exec unless auto mode is on
• Analytics are on by default, and the docs and README don't mention them
• No changelog and no release tags

Pros

• Official PyPI wheels with stated platforms
• Locked Cargo and uv dependencies and pinned toolchains
• Early-beta status stated in the docs

Cons

• No changelog or release tags
• Public repository is a sync of internal sources
• Extension API also labelled early beta
• Issue tracker unchecked

Pros

• Runs with no sign-up against a keyless local endpoint
• Works with Reflection, OpenRouter, OpenAI, Anthropic or any OpenAI-compatible endpoint
• Provider keys are kept out of commands the agent runs
• Manual approval is the default for shell commands and writes

Cons

• The first run in each directory is interactive, so an unattended agent cannot start cold
• In manual mode, approval calls fail in exec unless auto is on
• The default Reflection API was a free public beta with daily limits on 17 October 2026
• Approval mode is saved globally, so auto in one directory applies to later launches everywhere

Pros

• Keys shown once, revocable and disabled when their creator leaves
• reflection-data-retention header reports the mode on each response
• Weights can be self-hosted under Apache-2.0 with no account

Cons

• Terms license training on free use while the safety page says opt-in
• Flagged-content retention differs between terms and safety page
• No zero data retention yet
• No security.txt or bug bounty of its own

Pros

• Error reference states whether each code is retryable
• x-should-retry and x-request-id on responses
• Status page on incident.io with an RSS feed

Cons

• Three API incidents between 14 and 16 October 2026, two rated critical
• Per-organisation limits and the beta allocation are unpublished
• A tool-call turn returned without reasoning_content makes later requests in the session fail

Pros

• The error reference lists every status and error.code with retry advice
• Unknown parameters return 400 unsupported_parameter
• llms.txt, a Markdown copy of every page and a docs MCP endpoint
• reasoning_effort is an enum, and strict json_schema limits are listed

Cons

• stop, seed, user, metadata and the prompt_cache_* options are accepted and ignored
• Reasoning is always on and defaults to max, and none and minimal return 400 unsupported_value
• A second base URL, https://api.reflection.ai/v1, is named with no endpoints documented
• No changelog or release notes were found

Pros

• Free during the public beta
• 30 days' notice promised before fees rise
• Weights are Apache-2.0 and ungated, so self-hosting has no licence fee
• Rate-limit headers report remaining capacity

Cons

• No allocation figures, rate limits or post-beta price are published
• Reasoning can't be turned off, and the default effort is max
• Some organisations must verify a credit card before keys work
• Self-hosting guides use four B300 GPUs with NVFP4 weights

Pros

• Expiring keys with permissions chosen from 11
• Integration keys confined to one site
• The read-only run refuses tools that write
• Website logins entered on a protected page, never returned to a model

Cons

• Stores website passwords, authenticator secrets and recovery codes
• No security.txt, SOC 2 report or bug bounty found
• No server-side approval for writes to live sites
• Privacy policy unchecked

Pros

• 46 public read-only tools across 23 sites run with no account
• Tool outputs are checked against each tool's schema
• The errors page documents which site categories builds refuse
• find_website_tool returns possible_matches before a build

Cons

• The homepage lists bank portals and government filings, which builds refuse with site_not_supported
• find_website_tool searches only Pomerado's own catalogue
• Results are returned once and erased within 60 minutes if unread
• The 14 signed-in tools were taken from the docs and not checked

Pros

• Only runs that end with a result count
• Free plan and keyless use need no card
• Over-limit calls get 429 with reset_at, so spend stays bounded

Cons

• No per-call price or overage rate
• Business pricing is custom
• Yearly Premium price wasn't shown
• Keyless daily limit number wasn't found

Pros

• Public read-only tools run with no account, key or card
• Device sign-in gives an agent without a browser a 30-day key once a person approves
• Signed webhooks and get_job with wait_seconds cover both push and polling
• write_status and outcome_unknown say whether a write may have happened

Cons

• A result is returned once and erased after 60 minutes if unread
• Premium checkout is a Stripe link a person opens
• Builds for bank, government and ticket sites are refused, though the homepage lists bank portals and government filings

Pros

• MCP uses OAuth with PKCE and two scopes
• Docs tell the agent to treat transcripts and mid-call questions as data
• Each call can be read back with its transcript, notice and charge

Cons

• One REST key per account with no scopes and no self-serve rotation
• Confirmation before dialling is guidance only
• No security.txt, bug bounty or certification
• Default notice does not say the caller is an AI, contrary to the product page

Pros

• Example bodies for every documented error, and request examples for both call shapes
• llms.txt and a 79 KB Markdown rendering of the whole reference
• llms.txt and the skill both tell the agent to treat transcripts, summaries and mid-call questions as data

Cons

• slots is free-form, with its required keys listed only in prose
• POST /v1/places/suggest and the recording download are in the README but not in the spec
• The MCP tool definitions and annotations sit behind sign-in and were not read
• The product page claims AI disclosure out of the box, while llms.txt says the default notice does not say the caller is an AI

Pros

• Charges only for calls that reach a person
• Public /v1/pricing endpoint and per-call prices
• A new key includes 2,500 credits, 250 calls, with no card
• Credits never expire

Cons

• Each call needs 30 available credits as a hold
• The product page's per-call rates for the 2.5K and 5K packs don't match the pack labels
• Packs start at $100 for 10,000 credits, bought through Stripe checkout
• A 402 from POST /calls is an insufficient-credit error, not a payment challenge

Pros

• Key request needs only a name and email, with no card
• A new key includes 250 calls
• Per-call prices are public, with a /v1/pricing endpoint
• Charges apply only to calls that reach a person

Cons

• The key arrives by email, so an agent needs an inbox it can read
• One key per account, with no scopes and no self-serve rotation
• Credit top-ups go through Stripe checkout
• MCP tool definitions sit behind sign-in and were not read

Pros

• Request limit stated, and a retry is safe because inference has no side effects
• Separate 429 codes for allocation and capacity
• rejectIfBusy to fail fast

Cons

• No Retry-After documented for the capacity 429
• Alpha label with no deprecation policy, and Workers AI has retired models at 13 to 22 days' notice
• No SLA, and incident history before 7 October is unread

Pros

• temperature, tool_choice and response_format are typed on Workers AI
• Cards say what Mini and Max are for
• Examples in TypeScript, Python and curl, with vLLM recipes for both sizes

Cons

• Input schema and examples contradict each other
• Defaults work against the caller, with sampling on and Max needing explicit kwargs
• No limitations section, and English-only appears in metadata only

Pros

• Mini's rates are published without a login
• Daily free allowance covers about 1.8 million input tokens
• Weights are free under BSD-2-Clause (Mini) and OpenMDW-1.1 (Max)

Cons

• Max has no per-token price
• No cached-input price listed
• Whether Workers AI sign-up asks for a card is unchecked
• Baseten and SageMaker routes weren't priced

Pros

• Version named in the Workers AI model ID
• Alpha 1 weights remain published
• FP8 weights shipped with Alpha 2, as requested

Cons

• No changelog, notice period or deprecation plan
• Alpha 1 discussions unanswered
• Workers AI retirements have come with 13 to 22 days' notice
• No CI or tests for the weights visible

Pros

• Never merges its own fix PR
• Proofs run in a throwaway cloud copy
• Capture token revocable and uploads can be turned off
• Secret paths left out of snapshots

Cons

• Captures every repository by default
• What Captain may do to a running agent is undocumented
• Self-updater on by default
• No security.txt, bug bounty or certification

Pros

• parallax.yml keys listed with allowed values
• Skip reasons each come with a fix
• Review docs explain sessions, evidence states and retention at length

Cons

• No OpenAPI file, schema or published base URL
• No documented agent interface for the app
• HTTP error codes undocumented

Pros

• $50 credit and 5 free episodes on sign-up
• Retries of an episode use no extra credit
• Gateway token prices are public without a key

Cons

• Per-episode price shown only after sign-in
• Review API base URL and endpoint prices are not public
• Credit is bought by card through Stripe, with no x402
• A person must download the app and install the GitHub App

Pros

• Signed, notarised builds with SHA256SUMS
• Semver tags
• Docs describe the hosted review architecture

Cons

• Self-updater on by default with no release notes
• No status page, and the uptime page covers upstream providers only
• Hosted review runs on a single machine
• Issue tracker unchecked

Pros

• Fresh VM per job, deleted afterwards
• Host lane is opt-in with idleness and camera checks
• The skill lists actions to ask the person about first

Cons

• Guest SSH defaults to admin and admin
• No guest network or egress policy documented
• [prepare] run executes on the host with the caller's environment
• Not notarised, and the cask strips the quarantine attribute

Pros

• The exit-code table says what to do for each code
• Troubleshooting entries quote the error text, and a failure before the command starts repeats the last 20 lines
• offscreen check validates the project contract and rejects unknown keys without starting a VM

Cons

• status and image ls JSON field names may change before 1.0, with no JSON Schema
• Phases go to stderr and are hidden when stderr isn't a terminal, and stdout carries the wrapped command's full output
• Task commands are free shell text by design
• No changelog file and no llms.txt

Pros

• CLI and daemon negotiate a protocol number
• Unit tests run before GoReleaser publishes
• Beta status and possible changes stated in the README

Cons

• No changelog file
• One maintainer wrote all 116 commits
• A daemon restart fails active and attached queued jobs
• Cask's Tart dependency moved to openai/tools/tart on 15 October

Pros

• Exit codes separate the command's result from a queue timeout (75) and an Offscreen failure (70)
• Screenshots, logs and .xcresult bundles land in one directory per job
• --detach, status and cancel let an agent queue work and come back

Cons

• Install, app launch and the Local Network grant need a person
• A daemon restart fails active and attached queued jobs
• Apple silicon, macOS 14 or later and full Xcode only, with at most two VM jobs at once

Pros

• Request and daily limits stated on the model page
• Status page with a readable history of two minor incidents in 90 days
• Weights can be self-hosted for production

Cons

• No 429 or Retry-After behaviour documented
• Hosted route is for prototyping only, with no SLA
• Limits vary with other users' traffic, and trial terms were unread

Pros

• OpenAPI 3.1 file with enums and ranges on the main fields
• Python, LangChain, Node and curl examples with responses
• llms.txt and Markdown copies of the model page and API reference

Cons

• Card and snippets disagree on the medium reasoning switch
• No 429 or Retry-After body documented
• Hosted page lists 262K context where the card says 1M

Pros

• Hosted endpoint is free with no card
• Production routes are priced in public
• Weights run anywhere under a permissive licence

Cons

• The free endpoint can't be used in production
• The NVIDIA API Trial Terms were not read
• Reasoning defaults to on, so output tokens grow
• No keyless route, and the key needs a signed-in person

Pros

• Status page with a readable incident history
• Recipes for four serving stacks on release day
• NIM container refreshed every two weeks, per NVIDIA

Cons

• No deprecation notice periods for catalogue models
• Early access on the hosted page, v1.0 GA on the card
• Card's vLLM command also names a nightly image
• Hosted trial is for prototyping only

Pros

• No cloud credentials for analysis, planning or scaffolding
• Read-only plan identity and separate apply identity, OIDC with no static keys
• foundation-apply refuses updates, replacements and deletes

Cons

• Experimental release can use operator credentials from a workstation
• One maintainer and no staffed security response time
• What estimate sends to Infracost is unchecked

Pros

• INSTALL.md puts the always-on hook context at about 280 tokens, with the skill and two references loaded when needed
• Errors often name the next step, and the ceiling error lists four ways to bring the total down
• Regeneration refuses to overwrite an edited file and writes a .neckbeard-new copy

Cons

• Errors are single error: lines with no catalogue
• Exit codes are only 0, 1 and 2, with none per failure class
• Command output is text, with no JSON flag
• No changelog file and no llms.txt

Pros

• Free under Apache-2.0 with nothing to buy
• Context cost is stated, about 280 tokens always on
• The cost table comes before any file is scaffolded
• No cloud credentials needed for analyse, plan, scaffold and validate

Cons

• Estimates need a signed-in Infracost 0.10.x CLI
• What estimate sends to Infracost's pricing API was not checked
• The monthly figures are the project's own, not ours
• Applied infrastructure is billed by the cloud provider

Pros

• Catalogue versioned separately under a written semver contract
• Dependabot weekly and actions pinned by SHA
• CI runs a six-lane plan, scaffold and validate matrix

Cons

• 0.2.0 layout change not marked as breaking
• No changelog file
• Pre-alpha with one maintainer
• Estimates need the older Infracost 0.10.x CLI

Pros

• Per-agent keys stored as SHA-256 hashes
• Write, destructive and financial calls fail closed
• Kill switch on every tier
• Append-only ledger with signed receipts

Cons

• Agent key in the URL query string on the MCP route
• Policies and approvals enforce only on paid plans
• No injection mitigation for tool results
• security.txt returns 404, and no certification

Pros

• Fail-open and fail-closed defaults per action class
• x-navige-transaction counts retries once
• Degraded decisions are logged with a cause

Cons

• Status page monitors the retired host, with 7.221 per cent uptime under an all-online header
• No rate-limit numbers, Retry-After or backoff guidance
• Terms leave service levels as TBD