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 cenconq25/claude-code-app-studio --skill skill-improvegit clone --depth 1 https://github.com/cenconq25/claude-code-app-studioWrote 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/cenconq25/claude-code-app-studio/skill-improve)<a href="https://agentmods.dev/skills/cenconq25/claude-code-app-studio/skill-improve"><img src="https://agentmods.dev/badge/skills/cenconq25/claude-code-app-studio/skill-improve/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/cenconq25/claude-code-app-studio/skill-improve"><img src="https://agentmods.dev/badge/skills/cenconq25/claude-code-app-studio/skill-improve.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 | $0.00049 | $0.01540 |
| Opus 5 | $0.00024 | $0.00770 |
| Sonnet 5 | $0.00010 | $0.00308 |
| Haiku 4.5 | $0.00005 | $0.00154 |
Grade A, and why
skill-improve 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 6d 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Improve
A maintenance skill for the skill library itself. Combines static linting (frontmatter compliance, structure rules) with a fix-test-keep loop. Use when an existing skill is producing poor results, when template structure changes and skills need to follow, or when a skill has decayed against new conventions.
Phase 1: Pick the Target
Parse the argument:
<skill-id>— work on that skill at.claude/skills/<id>/SKILL.md.--all— iterate through every skill in the directory.--static-only— run only the linter, no rewrites.
If no argument is provided, list every skill and ask the user.
Read in parallel:
- The target SKILL.md.
- A reference set of skills already known to be in good shape (3-4 of
the simplest, like
/helpand/sprint-status). - Any local
skill-conventions.mdif present.
Phase 2: Static Lint
Delegate the structural checks to /skill-test --mode static <skill-id>.
That skill is the canonical lint runner for the library — it owns the
frontmatter rules, body rules, and severity scoring. This skill consumes
its report and decides what to fix.
Run:
/skill-test --mode static <skill-id>
Read the resulting verdict and the per-rule findings. Capture: rule id, severity (BLOCKER, WARNING, NIT), short description, suggested fix hint.
If /skill-test is unavailable for any reason, fall back to inlining the
checklist (see /skill-test SKILL.md for the canonical rule set):
frontmatter compliance (name, description, argument-hint,
user-invocable, allowed-tools, model, agent), body compliance
(H1, purpose paragraph, numbered phases, Quality Gates, Examples, Next
Steps, line count 150-450, no emoji).
Phase 3: Convention Lint
Cross-check against the rest of the library:
- Does the skill claim agents/tools that exist?
- Does it reference paths that match the project's directory structure?
- Does it use the project's standard verdict tiers (PASS/CONCERNS/FAIL or APPROVED/etc.)?
- Does it use AskUserQuestion at decision points where the reference skills do?
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.
- 6d ago First seen · 241 lines · 49 tokens per session scan A f156c6700672
skill-improve is a skill published in the GitHub repository cenconq25/claude-code-app-studio (40 stars, last pushed 4mo ago), licensed MIT. It adds 49 tokens to every session and 1,540 once invoked, about $0.0002 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 2026-09-03.
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