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 oaustegard/claude-skills --skill declaudinggit clone --depth 1 https://github.com/oaustegard/claude-skillsWrote 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/oaustegard/claude-skills/declauding)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/declauding"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/declauding/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/oaustegard/claude-skills/declauding"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/declauding.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00225 | $0.05613 |
| Opus 5 | $0.00112 | $0.02806 |
| Sonnet 5 | $0.00045 | $0.01123 |
| Haiku 4.5 | $0.00022 | $0.00561 |
Grade A, and why
declauding 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 today.
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 — 408 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Declauding
Turn LLM-shaped prose into prose a human technical writer would have written.
Two output modes:
- clean (default) — the rewritten text, nothing else.
- annotated — a single-file HTML artifact: rewritten text, every changed passage marked, each with the original, the tic name, and why it goes. A toggle hides the marks so the result can be read straight through.
Three ways it gets called, which change what you deliver:
- Pasted text (default) — the user gives text in the conversation. Return the rewrite, plus a short list of what changed if the edit was substantial.
- File — the user points at a path. Rewrite the file in place and report a summary in the conversation rather than pasting the whole result back. Edit prose only: leave code blocks, frontmatter, data, link targets and quoted specimens alone.
- Embedded — another skill or agent is calling this as one step of a larger job (a PR description, a commit message, a doc). Return the final text and nothing else. No preamble, no summary, no tic list.
Do not invent specifics
The rewrite must not contain a fact, name, number, date, quote or citation that is not in the source. This is the failure mode the skill invites rather than prevents: the fix for a vague sentence is a specific one, and the specific has to come from the source or from the author.
Experts believe it plays a crucial role becomes the sources here do not say who studies it, or gets cut. It does not become researchers at Lanzhou University unless the source says so. When a sentence needs real-world detail to work, ask for it or write the plain version without it.
Opinions and stance count as voice rather than fact. Keeping the author's judgment is required (see Overcorrection); adding a factual claim they did not make is a defect even when the result reads more human.
The one pattern
Almost every tic in references/register.md is a version of the same move:
the sentence is built to make the reader feel a finding arrive, instead of
stating the finding.
What ships with it
16 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.
- assets/annotated.template.html 5.1 KB
- assets/staging-axis.json 4.7 KB
- CHANGELOG.md 29 KB
- README.md 19 KB
- references/annotating.md 3.1 KB
- references/corpus.md 5.4 KB
- references/preservation.md 5.3 KB
- references/register.md 45 KB
- scripts/declaude_diff.py 12 KB runs code
- scripts/declaude_lint.py 51 KB runs code
- scripts/declaude_rank.py 7.0 KB runs code
- scripts/declaude_review.py 11 KB runs code
- tests/sample-clean.md 1.7 KB
- tests/sample-structure.html 397 B
- tests/sample-structure.md 846 B
- tests/sample-tics.md 9.4 KB
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.
- today Changed · +3 lines 030ebf2e7a6b
- 10d ago First seen · 405 lines · 225 tokens per session scan A 1ca889e6b9c7
declauding is a skill published in the GitHub repository oaustegard/claude-skills (148 stars, last pushed today), licensed MIT. It adds 225 tokens to every session and 5,613 once invoked, about $0.0011 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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