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 extractgit 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/extract)<a href="https://agentmods.dev/skills/cenconq25/claude-code-app-studio/extract"><img src="https://agentmods.dev/badge/skills/cenconq25/claude-code-app-studio/extract/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/extract"><img src="https://agentmods.dev/badge/skills/cenconq25/claude-code-app-studio/extract.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 | $0.00058 | $0.01936 |
| Opus 5.5 | $0.00023 | $0.00774 |
| Sonnet 5.5 | $0.00012 | $0.00387 |
| Haiku 4.5 | $0.00006 | $0.00194 |
Grade A, and why
extract 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 1mo 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extract — Code Pattern Capture
Reads existing implementation and produces a system.md describing how the code is actually built — not how it should be. This is descriptive, not prescriptive.
Output: design/extracted/<system-or-area>.md
Purpose / When to Run
Run when:
- A brownfield project has working code but no design docs
/reverse-documentis running and needs the extracted patterns as input- The team wants a "this is how we currently do it" snapshot before making a change
Distinct from /design-system (which authors a forward-looking PRD) and /architecture-decision (which records a deliberate decision). This skill captures observed reality so a future PRD or ADR can be written against an honest baseline.
Inputs
- Required: a path or glob pointing to the source files to analyze (e.g.,
src/screens/auth/,lib/features/onboarding/**/*.dart) - The framework (read from
.claude/docs/technical-preferences.md)
Outputs
design/extracted/<system-name>.md
Phase 1: Resolve Scope
If no path was passed, ask:
- Prompt: "Which area of code should I extract patterns from?"
- Options:
Screens / pages—src/screens/**,lib/features/**,app/Sources/**/Views/State management— wherever the app's stores / view models liveNetworking / API client— fetchers, interceptorsNavigation— routing config, deep linksSpecific subdirectory— free text path
Use Glob to confirm the target exists and resolve to a list of files. Cap at ~50 files for one extraction; if more, sample and ask whether to chunk.
Determine the system name from the path (e.g., src/screens/auth/ → auth).
Phase 2: Read & Skim
Read each file. For each, classify by role: screen, component, hook/composable, store, service, util, type definition, test.
While reading, build a fact table per file:
- Imports (which dependencies and from where)
- Exported names
- State shape (if a store)
- Side effects (network calls, persistence reads/writes, navigation)
- Error handling pattern
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.
- 1mo ago First seen · 232 lines · 58 tokens per session scan A 6329e76bc988
extract is a skill published in the GitHub repository cenconq25/claude-code-app-studio (42 stars, last pushed 5mo ago), licensed MIT. It adds 58 tokens to every session and 1,936 once invoked, about $0.0002 per session on Opus 5.5. 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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