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 skills add Cristhianzl/claude-skills-czl --skill documenting-featuresgit clone --depth 1 https://github.com/Cristhianzl/claude-skills-czlWrote 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/cristhianzl/claude-skills-czl/documenting-features)<a href="https://agentmods.dev/skills/cristhianzl/claude-skills-czl/documenting-features"><img src="https://agentmods.dev/badge/skills/cristhianzl/claude-skills-czl/documenting-features/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/cristhianzl/claude-skills-czl/documenting-features"><img src="https://agentmods.dev/badge/skills/cristhianzl/claude-skills-czl/documenting-features.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 | $0.00089 | $0.02433 |
| Opus 5 | $0.00044 | $0.01216 |
| Sonnet 5 | $0.00018 | $0.00487 |
| Haiku 4.5 | $0.00009 | $0.00243 |
Grade A, and why
documenting-features 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 12d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documenting Features
Generate one Markdown file per feature, covering all 10 sections, written so Product can validate the first half and Engineering can maintain the whole thing. Lives next to the code, version-controlled, kept in sync with implementation.
Read first (always)
List learnings/ and read every file relevant to the current feature (the domain, the bounded context, the team). Project-specific naming conventions, ADR numbering, glossary inheritance rules, or template variants live there and override the defaults in this SKILL.md. If a learning conflicts with this file, the learning wins — mention it to the user.
Tradeoff — when to apply, when to lighten up
Apply the full 10-section template for shipped features that cross team boundaries (Product ↔ Engineering ↔ Ops) or touch the domain model.
Lighten formality (skip sections, not principles) for: internal tooling not exposed to users; refactors with no behavior change (document the ADR only); spike work and prototypes behind feature flags. Never skip Section 1 (Overview) and Section 2 (Ubiquitous Language) — the glossary is the single source of truth for cross-team communication.
Core principles
- Ubiquitous language is the single source of truth. The same term across docs, code, database, and conversation. If the business calls it "Enrollment", the code has
class Enrollmentand the database has theenrollmentstable — no synonyms. - Documentation lives next to the code. Stored in the repo, version-controlled with the feature, kept in sync via PR review.
- One feature = one file. All 10 sections in a single
.mdfile. Use horizontal rules (---) and clear headers to separate sections. One-file-per-feature beats N-files-per-feature for navigation and synchronization. - C4 model for diagrams. Level 1 (Context) for Product/Stakeholders. Level 2 (Container) for both. Level 3 (Component) for Engineering.
Workflow
- Analyze the implemented feature. Read the production code, the tests, the PR description, the ADRs already in the repo. Identify the domain (bounded context), the actors, the inputs and outputs. → verify: you can name the bounded context and the related contexts.
What ships with it
5 files 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.
- 12d ago First seen · 135 lines · 89 tokens per session scan A a5622b058568
documenting-features is a skill published in the GitHub repository Cristhianzl/claude-skills-czl (5 stars, last pushed yesterday), licensed MIT. It adds 89 tokens to every session and 2,433 once invoked, about $0.0004 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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