# smolagents vs TradingAgents (slim)

> TradingAgents scores 61.4 (C) to smolagents's 58.7 (C) for agent frameworks. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/smolagents-vs-tradingagents.md (~4,300 tokens) · this version ~2,130 tokens · JSON https://www.anchorterminal.com/compare/smolagents-vs-tradingagents.json · canonical https://www.anchorterminal.com/compare/smolagents-vs-tradingagents
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
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TradingAgents scores 61.4 (C) on agent readiness against smolagents's 58.7 (C), and leads in 2 of 7 scored categories. smolagents leads on reliability, schema & documentation and agent ergonomics. Both do agent frameworks.

- smolagents: C 58.7, rank #735 of 1486 · https://www.anchorterminal.com/tools/smolagents.min.md
- TradingAgents: C 61.4, rank #614 of 1486 · https://www.anchorterminal.com/tools/tradingagents.min.md
- smolagents, good for Small Python projects and research that want code-writing agents with minimal abstraction. Ahead on Reliability, 64 against 52; Schema & documentation, 81 against 61; Agent ergonomics, 68 against 61. Also No key needed to call it.
- TradingAgents, good for Researchers who want a fixed multi-agent analysis of one listed instrument or crypto pair on a date, with point-in-time data for backtests, and who will run Python. Ahead on Maintenance & community, 78 against 34. Also No incidents deducted, where smolagents loses 6 points for them.

| Category | smolagents | TradingAgents |
| --- | --- | --- |
| Reliability (16%) | 64 | 52 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 81 | 61 |
| Agent ergonomics (13%) | 68 | 61 |
| Security & auth (14%) | 66 | 62 |
| Payments & pricing (10%) | 60 | 60 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 34 | 78 |
| Transparency & trust (7%) | 65 | 68 |

| Fact (where they differ) | smolagents | TradingAgents |
| --- | --- | --- |
| Vendor | Hugging Face | Tauric Research |
| Auth | None | API key |
| llms.txt | yes | no |
| Last release | 2026-05-29 | 2026-10-27 |
| Terms last updated | 2022-09-15 | 2026-10-23 |
| Privacy policy last updated | 2023-03-28 | 2026-10-23 |
| Terms or service can change without notice | yes | not found in the text |
| Popularity | 30k stars, 171k PyPI/wk | none |

Why the edge:
- Maintenance & community, TradingAgents +44: smolagents 34 (v1.26.0 on 29 May 2026, 161 days before this check (10). No release in the 90 days to 6 November (0). 416 open issues and 1,045 open issues and pull requests on 6 November, with 144 issues opened in the 90 days to 3 November. Of the 50 newest, 26 had a comment and 1 was closed. Two 2026 CVE records say the vendor didn't respond to the reporter, and seven commits reached main from 8 August to 6 November (6). Python only, and the package is the current one (10). CI with actions pinned to commit SHAs and Dependabot for actions (8). 10+0+6+10+8 = 34.); TradingAgents 78 (0.7.1 on 27 October 2026 (30). Seven releases in the 90 days to 2 November, 0.4.0 (31 August), 0.5.0, 0.5.1, 0.5.2, 0.6.0, 0.7.0 and 0.7.1 (20). The earlier issue and pull request counts came from shields.io and are struck. On the clone, fixes cite issue numbers and each release credits the people who reported or fixed them (15 outside contributors in 0.7.1), but 251 of the 258 commits since 4 August are by one maintainer's accounts and reply times couldn't be read (13 of 25, as pipecat on clone evidence). No PyPI package; versions ship as GitHub releases with a wheel since 0.7.0 (8 of 15). CI with tests, lint and a clean-install check; dependencies set lower bounds only and no Dependabot configuration is in the repository (7 of 10). 30+20+13+8+7 = 78.)
- Schema & documentation, smolagents +20: smolagents 81 (Framework reading. A typed Python API with reference pages for agents, models, tools and executors (22). llms.txt and Markdown pages on huggingface.co (10). The docs say when to use CodeAgent or ToolCallingAgent and when a sandbox is needed (17). Tools declare typed inputs in a schema dictionary or from a decorated function (12). Many runnable examples; error classes exist but aren't catalogued (10). Versions tagged with release notes, no changelog file (10). 22+10+17+12+10+10 = 81.); TradingAgents 61 (Framework reading. No API reference or docs site. Typed interfaces exist in the source, Pydantic models for the research manager's, trader's and portfolio manager's outputs and Annotated signatures on the twelve data tools, with no py.typed marker (10 of 25). The README and changelog are Markdown in the repository; no llms.txt (4 of 10). The README states limits plainly, that runs vary, which statements past-dated runs withhold and why, and that it is a research tool, not advice (15 of 20). Configuration is a plain dict of string keys, though environment overrides are coerced to the default's type and fail loudly on a bad value (8 of 15). Runnable Python and CLI examples throughout the README; the vendor error hierarchy is documented only in source docstrings (9 of 15). Dated changelog for every release from 0.1.0 with upgrade notes (15).)
- Reliability, smolagents +12: smolagents 64 (Local-package reading. Official PyPI package with Python 3.10 or newer (20). A public tests workflow runs pytest on Python 3.10 and 3.12 for pushes and pull requests; whether main passes wasn't read (15). 416 open issues and 1,045 open issues and pull requests on 6 November, with 144 issues opened in the 90 days to 3 November. Of the 50 newest, 26 had a comment and 1 was closed. Two 2026 CVE records say the vendor didn't respond to the reporter, and seven commits reached main from 8 August to 6 November (6). Release notes on GitHub tags but no changelog file, and the remote WasmExecutor was removed in a minor release (8). 1.0 since 31 December 2024 (15). 20+15+6+8+15 = 64.); TradingAgents 52 (Read with the local-software lines, because the owner runs it. Python 3.11 or later is stated and CI tests 3.11 to 3.14, but the project publishes no PyPI package. No workflow uploads one, and the README installs from a clone or Docker Compose. From 0.7.0 a release workflow builds a wheel and source archive from each tag and attaches them to the GitHub release (12 of 20). Public CI on every push and pull request runs the test suite (about 1,009 test functions at v0.7.1) on four Python versions and once in America/New_York, a clean-install import check and Ruff. The 25 October check read the pass state from shields.io, a third-party copy of GitHub data this run doesn't use, so that reading is struck, and the pass state on main is unread (15, as berth and agentvfs). Issue counts came from the same source and are struck too. On the clone, 0.7.1 (27 October) fixes 22 numbered issues, 17 of them above #1518, the newest fixed in 0.7.0 on 16 October, and credits 15 outside contributors; open crash or regression issues and reply times are unread (15, as berth on the same pattern). The changelog follows Keep a Changelog and Semantic Versioning and lists breaking changes under "Upgrading from", but 0.5.1, a patch release, moved import paths and removed classes (10 of 15). Version 0.7.1 with no stability statement (0). 12+15+15+10+0 = 52.)
- Agent ergonomics, smolagents +7: smolagents 68 (Framework reading. MCPClient loads an MCP server's tools in a few lines (20). max_steps, planning intervals and final_answer_checks bound a run (16). Errors from tools and code go back to the model as observations (14). No built-in retry, idempotency or resume beyond replaying memory (8). Few required parameters and many providers, Python only, and the default model needs a Hugging Face token (10). 20+16+14+8+10 = 68.); TradingAgents 61 (Framework reading, scored on what an outside agent needs to call it. No MCP client or server, so it can't be attached as tools; a run is four lines of Python (`TradingAgentsGraph(config=...).propagate(ticker, date)`) or one headless CLI command with flags (10 of 25). Analyst selection, debate and risk rounds (default 1), `max_tool_rounds` (20), `max_recur_limit` (100), article limits and `--no-html` size a run (14 of 20). A typed vendor error hierarchy separates unavailable from absent data, the headless CLI names the missing flag before a run starts, and an unparseable decision returns REVIEW rather than Hold (15 of 20). Checkpoint resume is opt-in, a backtest rerun with the same `run_id` skips finished cells, and settlement writes each decision once; nothing writes to an outside system (15 of 20). Sensible defaults, but the default provider is OpenAI's GPT-6 models with a key, and Python only (7 of 15).)