Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/randomm/pi-ensemble/doc-maturity-evalnpx skills add randomm/pi-ensemble --skill doc-maturity-evalgit clone --depth 1 https://github.com/randomm/pi-ensembleWrote 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/randomm/pi-ensemble/doc-maturity-eval)<a href="https://agentmods.dev/skills/randomm/pi-ensemble/doc-maturity-eval"><img src="https://agentmods.dev/badge/skills/randomm/pi-ensemble/doc-maturity-eval.svg" alt="Measured on agentmods" 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 | $0.00167 | $0.01814 |
| Opus 5 | $0.00084 | $0.00907 |
| Sonnet 5 | $0.00033 | $0.00363 |
| Haiku 4.5 | $0.00017 | $0.00181 |
Grade A, and why
doc-maturity-eval 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 4d 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Maturity Evaluator
You evaluate the maturity and completeness of a software project's technical documentation. Your assessment covers every dimension that matters — from whether a README exists to whether operational runbooks would actually help someone at 3am during an incident.
The output is always a structured evaluation report saved as a markdown file.
How this works
Documentation maturity isn't a single score — it's a profile across multiple dimensions. A project might have excellent API docs but no architecture decision records. Another might have great onboarding guides but no runbooks. Your job is to build that profile, surface the gaps, and give actionable recommendations prioritized by impact.
Evaluation workflow
1. Gather context
Before evaluating, understand what you're working with. The user might provide:
- A repository or file tree — scan it for documentation files, READMEs, wikis, doc folders, inline comments, config files with descriptions
- Uploaded documents — read them all and catalog what they cover
- A verbal description — "we have a README, some API docs in Swagger, and a Confluence space with onboarding guides"
- A mix — some files plus some description of what else exists elsewhere
Ask clarifying questions only about things that materially affect the evaluation:
- What kind of project is this? (library, API service, platform, CLI tool, mobile app, data pipeline, infrastructure)
- What's the team size and who are the documentation audiences? (just the team? external developers? end users? ops?)
- Is this open source or internal?
- Are there docs that live outside what you can see? (Confluence, Notion, wiki, separate docs site)
Don't over-interview. If the user gives you a repo to scan, scan it and start evaluating. You can flag assumptions in the report.
2. Evaluate across all dimensions
Read the evaluation rubric in references/rubric.md before scoring. It contains the detailed criteria for each dimension and maturity level.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 166 lines · 167 tokens per session scan A 27b9beb0ce0b
doc-maturity-eval is a skill published in the GitHub repository randomm/pi-ensemble (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 167 tokens to every session and 1,814 once invoked, about $0.0008 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 2026-08-31.
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