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-reviewer/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-reviewer)<a href="https://agentmods.dev/skills/strands-agents/harness-sdk/docs-reviewer"><img src="https://agentmods.dev/badge/skills/strands-agents/harness-sdk/docs-reviewer.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00068 | $0.01540 |
| Opus 5 | $0.00034 | $0.00770 |
| Sonnet 5 | $0.00014 | $0.00308 |
| Haiku 4.5 | $0.00007 | $0.00154 |
Grade A, and why
docs-reviewer scanned grade A with 0 findings 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 8d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Reviewer
Scope: Voice, style, structure, and terminology of drafts in progress. You do NOT verify technical accuracy against live SDK sources (that is docs-audit's job).
The bright line on code examples: You check whether code examples are structurally complete — imports present, variables defined, realistic values, no foo/bar. This is the Stripe completeness principle, a voice/style check. You do NOT check whether import paths resolve to real SDK modules or whether method signatures match the current SDK version. That verification is docs-audit's scope.
Procedure
- Read the draft provided by the user.
- Classify the content type (tutorial, how-to, explanation, reference) from frontmatter or structure.
- Score each of the five dimensions below.
- Assign a verdict.
- Output the structured review.
Five Review Dimensions
1. Voice Stack Compliance
Reference ../../references/voice-guide.md for the full layer definitions. Check:
- Structure: Does each section answer exactly one question? Flag mixed-purpose sections.
- Narrative flow: Start with why the topic matters and what use-case problems it solves. Throughout, show how to implement using Strands SDK in a self-contained, concise way.
- Framing: Does the first sentence of every section describe the developer's goal? Flag sections leading with API descriptions.
- Register: Is the tone appropriate for the content type?
- Constraints: Scan for banned phrases, em-dashes, passive voice, hedging. Apply type-aware overrides (passive in reference is fine; longer sentences in explanation are fine).
- Authenticity: Structural variety, visible editorial choices, concision.
2. Multi-Language Correctness
For pages with <Tabs> for Python and TypeScript:
- Prose between tabs is language-neutral. Flag prose inside a
<Tab>that names the language of that tab (e.g., "Python requires..." inside the Python tab). The reader chose the tab; they know. - Flag language-specific identifiers spelled out manually in shared prose — these should use the
<Syntax>component to adapt to the reader's language selection. - Headings describe the concept, not the API. Flag headings containing language-specific parameter names or syntax (e.g.
preserve_context=False,preserveContext: false). The table of contents should read the same regardless of language. - Callout boxes (
:::note,:::caution, etc.) meet the bar defined inmdx-authoring.md. Most facts belong as inline prose.
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.
- 8d ago First seen · 128 lines · 68 tokens per session scan A 7ee647e7ac0e
docs-reviewer is a skill published in the GitHub repository strands-agents/harness-sdk (7,168 stars, last pushed 3d ago), licensed Apache-2.0. It adds 68 tokens to every session and 1,540 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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