Strands Agents is an open-source SDK for building and running AI agents in Python and TypeScript. Developers use it to create agents with model providers, tools, lifecycle controls, memory, sessions, streaming, tracing, and evaluations, and the catalogue includes add-ons for its agent-building workflow.
Borrowing it
Nothing to install: this file belongs to strands-agents/harness-sdk. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/strands-agents/harness-sdk/main/.agents/skills/docs-verifier/SKILL.mdgit clone --depth 1 https://github.com/strands-agents/harness-sdkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/strands-agents/harness-sdk/docs-verifier)<a href="https://agentmods.dev/skills/strands-agents/harness-sdk/docs-verifier"><img src="https://agentmods.dev/badge/skills/strands-agents/harness-sdk/docs-verifier/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/strands-agents/harness-sdk/docs-verifier"><img src="https://agentmods.dev/badge/skills/strands-agents/harness-sdk/docs-verifier.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.03114 |
| Opus 5.5 | $0.00021 | $0.01246 |
| Sonnet 5.5 | $0.00011 | $0.00623 |
| Haiku 4.5 | $0.00005 | $0.00311 |
Grade C, and why
docs-verifier scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf .context/verify .context/verify-venv .context/src harness-ts/.verify How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Verifier
Check that everything a documentation page states is true of the code right now, and produce a claim-by-claim report citing the file:line behind each assessment. Unlike docs-reviewer (style) and docs-audit (whether a page needs work), this skill checks only truth, and checks all of it. Where the page and the code disagree, the page is wrong; never edit source to match a page.
Inputs
Verify exactly the pages you're given, usually one or two:
- page paths under
site/src/content/docs/(or their URLs) - a docs PR or branch: its changed pages, from
git diff --name-only origin/main... -- site/src/content/docs - a code change: pages whose
sourceLinksor prose mention the changed paths or symbols (grep -rln "<path>\|<Symbol>" site/src/content/docs)
With no target, ask. Never default to the whole site.
Where the truth lives
| Area | Source | Public surface |
|---|---|---|
Python SDK (strands-agents) |
strands-py/src/strands/ |
__all__ of the imported module |
TypeScript SDK (@strands-agents/sdk) |
strands-ts/src/ |
strands-ts/src/index.ts (@internal is not public) |
Python harness (strands-harness) |
harness-py/src/strands_harness/ |
harness-py/src/strands_harness/__init__.py |
TypeScript harness (@strands-agents/harness) |
harness-ts/src/ |
harness-ts/src/index.ts (./internal is not public) |
CLI (@strands-agents/cli) |
strands-cli/src/ |
strands-cli/src/cli/; in-chat slash commands in strands-cli/src/tui/chat/commands.ts |
MCP server (strands-agents-mcp-server) |
strands-mcp/src/strands_mcp_server/ |
its registered MCP tools |
Not in this repo: user-guide/evals-sdk/, user-guide/box/, and user-guide/shell/ document strands-agents/evals, strands-agents/box, and strands-agents/shell. Shallow-clone the repo into .context/src/<repo> or read it with gh api repos/strands-agents/<repo>/contents/<path>, and cite <repo>/<path>:line. A package name alone never makes a claim correct.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 208 lines · 53 tokens per session scan C 6c41d9472178
docs-verifier is a skill published in the GitHub repository strands-agents/harness-sdk (8,996 stars, last pushed today), licensed Apache-2.0. It adds 53 tokens to every session and 3,114 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-21.
Other skills, from other repositories
verify-changes
Verify code changes by running the project's typecheck, build, lint, and targeted tests, then fix and re-run until clean. Use after editing any source file.
agent-eval
Use when measuring whether an LLM or agent system actually got better and gating merges on it: golden sets, fixing an inflated LLM-as-judge, scoring RAG (faithfulness, contextual recall) or agent trajectories (tool correctness, completion), or picking an eval framework. NOT building the agent loop, tools or RAG…
returns-policy
Answer return, refund, and warranty questions for electronics. Use when the user mentions returns, refunds, RMAs, warranty coverage, damaged items, or opened packaging.
technical-troubleshooting
Provide setup, troubleshooting, and maintenance guidance. Use when the user reports a device that won't power on, connectivity issues, setup questions, overheating, or maintenance concerns.
deepeval
Use when discussing or working with DeepEval (the python AI evaluation framework).
browser-qa
Testing web apps through a real browser: reconnaissance before acting, selector discovery, state capture, console errors and screenshot evidence. Use on a web surface end to end, or to reproduce a front-end bug.