# agents-tree vs DeepEval (slim)

> DeepEval and agents-tree score within a point of each other for agent tracing, 64.9 and 64.3 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/agents-tree-vs-deepeval.md (~4,200 tokens) · this version ~2,080 tokens · JSON https://www.anchorterminal.com/compare/agents-tree-vs-deepeval.json · canonical https://www.anchorterminal.com/compare/agents-tree-vs-deepeval
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-01
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

DeepEval and agents-tree score within a point of each other on agent readiness, 64.9 (B) and 64.3 (B). agents-tree leads on security & auth. Both do agent tracing.

- agents-tree: B 64.3, rank #401 of 1260 · https://www.anchorterminal.com/tools/agents-tree.min.md
- DeepEval: B 64.9, rank #367 of 1260 · https://www.anchorterminal.com/tools/deepeval.min.md
- agents-tree, good for Seeing every coding-agent session and its sub-agents as one tree in a terminal Ahead on Security & auth, 66 against 47. Also No key needed to call it.
- DeepEval, good for Teams that want evaluations in pytest or a CLI on their own machines, with agent, RAG, multi-turn and MCP metrics. Ahead on Schema & documentation, 78 against 64; Maintenance & community, 83 against 63. Also Free to start without a card.

| Category | agents-tree | DeepEval |
| --- | --- | --- |
| Reliability (16%) | 60 | 59 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 64 | 78 |
| Agent ergonomics (13%) | 73 | 72 |
| Security & auth (14%) | 66 | 47 |
| Payments & pricing (10%) | 60 | 60 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 63 | 83 |
| Transparency & trust (7%) | 62 | 66 |

| Fact (where they differ) | agents-tree | DeepEval |
| --- | --- | --- |
| Kind | Agent framework | SDK + MCP |
| Vendor | Karel Blavka | Confident AI, Inc. |
| Auth | None | OAuth or key |
| Pricing | Free | Freemium |
| Price for agent tracing | free | $1 per GB per month |
| Licence | MIT (Copyright (c) 2026 Karel Blavka) | Apache 2.0 for the Python and TypeScript packages and the agent skills. Confident AI, the hosted platform, is a proprietary service under its own terms |
| Read-only variant documented | yes | no |
| llms.txt | no | yes |
| Last release | 2026-10-08 | 2026-10-02 |
| Terms last updated | couldn't be read | no document linked |
| Customer content may train models | couldn't be read | not read yet |
| Terms restrict automated access | couldn't be read | not read yet |
| Terms restrict benchmarking | couldn't be read | not read yet |
| Terms or service can change without notice | couldn't be read | not read yet |
| Arbitration or class-action waiver | couldn't be read | not read yet |
| Popularity | none | 19k stars, 35k npm/wk, 736k PyPI/wk |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Maintenance & community, DeepEval +20: agents-tree 63 (1.2.0 on PyPI on 8 October 2026, 24 days before the check, and a commit on main on 11 October (30). Five PyPI releases between 7 and 8 October 2026 (20). Issue and pull-request replies couldn't be read, as github.com was unreachable. The bare clone shows two Dependabot branches of 28 October unmerged (5 of 25). Not an MCP server and in no official directory; herdr's plugin marketplace couldn't be read (0). No runtime dependencies, a lock file, CI on five Python versions and Dependabot for the workflow actions, with its two updates unmerged (8 of 10). 63 in all.); DeepEval 83 (Python 4.2.8 was tagged on 2 October 2026, seven days before the check (30). 14 Python releases tagged since 9 August, from 4.1.6 to 4.2.8 (20). 124 commits in the 30 days to 9 October, most by three maintainers, and a Discord community. 322 issues and 387 pull requests are open and reply times were not read (14). Current official packages in Python and TypeScript, the latter at 0.9.21 on 30 September (15). A `poetry.lock` file and CI on pull requests. No Dependabot configuration was found and the core test workflow is failing on main (4).)
- Security & auth, agents-tree +19: agents-tree 66 (Harness reading of the framework checklist, as agent-tree and superpowers were read. 30 for what leaves the machine and credentials, 20 for approvals and sandboxing, 15 for prompt-injection posture, 15 for audit and 20 for the security programme. No credentials, no network code and no runtime dependencies; PyPI releases are built by trusted publishing with no stored token and wait for a maintainer to approve the pypi environment. It reads every transcript of four agent CLIs, prompts included, and the herdr plugin runs the repository's bundled source rather than a PyPI release (26). Read-only by design. SQLite files are opened with mode=ro, nothing is written to an agent's files, and the only writes are a pane mark (directory 0700, file 0600, O_NOFOLLOW) and herdr's config block with a backup and check. It can't act on an agent (17). Control characters and escape sequences are stripped from every transcript field before a view, and the help warns that output run inside an agent lands in its context, but `--json` passes prompts and last messages unredacted with no note that they are untrusted (10). It keeps no state or log of its own. The detail view names each transcript's path, and herdr's config keeps a backup (8). No SECURITY.md, no security.txt and no advisories found; GitHub's security page couldn't be read. CI pins third-party actions to commit SHAs with Dependabot on them (5). 66 in all.); DeepEval 47 (Local runs need no credential. Provider keys and `CONFIDENT_API_KEY` are read from the environment or a dotenv file, and storing keys in the legacy `.deepeval/.deepeval` file is deprecated in the source. Confident AI project keys take a name and an expiry and can be deactivated, rotated with a grace period or deleted. No per-permission scopes were found (20). The framework has no read-only mode. Once logged in, test runs and traces upload to Confident AI (8). Metrics pass application output to an LLM judge, and no guidance on untrusted content reaching the judge was found in the pages read (5). Each run is recorded in local JSON or SQLite. Confident AI documents audit log exports, which we did not read (7). GitHub shows no security policy and no published advisories, and security.txt answered 404 on both domains. No bug bounty was found. The Confident AI site states SOC 2 Type II and HIPAA, and its trust centre is drawn by script and was not read (7).)
- Schema & documentation, DeepEval +14: agents-tree 64 (Framework reading, docs a model can follow, as agent-tree was read. `--json` writes one document with `schema_version` 1 and a fixed set of session, agent and detail fields, and model.py types them as dataclasses, but no JSON Schema or field reference is published (14 of 25). README, AGENTS.md and docs/demo are Markdown in the repository; no llms.txt (10). The README says what it shows and reads, has a caveats section per provider (context window inference, internal formats, how running sessions are found), and the command's help says not to run it inside an agent (15 of 20). argparse with choices for --provider and --color, positive-number checks for --window and --interval, and --json refused with --watch (10 of 15). Usage examples for every flag, key and column tables, and errors as messages on stderr with exit code 1, with few error outputs documented (10 of 15). Semver tags and a schema version, no changelog (5 of 15). 64 in all.); DeepEval 78 (Read on the framework lines. The Python package ships `py.typed` and pydantic models, the TypeScript package ships type declarations, and the CLI is built on typer. A library has no OpenAPI file to publish (18). llms.txt on deepeval.com indexes the docs, and pages carry a Copy Markdown control (10). Each metric has its own page with required parameters and usage, and three agent skills in the repository tell a coding agent how to add evaluations and tracing (16). Typed test case and metric classes, with enums for evaluation parameters and CLI choices (12). Many runnable examples, a troubleshooting page and an environment variable reference. Error types are not listed in one place (11). Tagged releases for both packages and a public changelog by year, but the 2026 changelog stops at 4.2.0 of 25 August and has no entry for 4.2.1 to 4.2.8 (11).)