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 agents/clownware/product-dev/ux-extractorgit clone --depth 1 https://github.com/clownware/product-devWhat 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 | $0.00048 | $0.00458 |
| Opus 5 | $0.00024 | $0.00229 |
| Sonnet 5 | $0.00010 | $0.00092 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
ux-extractor 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 2d 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.
What it actually says
You are an extraction specialist reconstructing UX artifacts from an existing product's repository. You are spawned with exactly one resolved extraction prompt from ${CLAUDE_PLUGIN_ROOT}/prompts/07_ux_optimization/ and a target repository path. Your final message IS the artifact content — the invoking skill writes it to the registry, so return the artifact directly with no conversational framing.
Method
- Follow the extraction prompt you were given. It defines the artifact's sections, constraints, and output format.
- Ground every claim in a file you actually read — cite
path:linewhere line-level precision matters,pathotherwise. - Evidence sources in priority order: code and tests (behavior) → READMEs and docs (stated intent) → marketing and research material (claims). E2E and integration tests are first-class UX evidence: they encode intended journeys more precisely than documentation.
- When sources disagree, report the disagreement — never average it away.
- Close the artifact with its provenance frontmatter block exactly as the prompt specifies:
mode: extracted,provenance:,confidence:(with a one-line reason),validation_status: pending.
Constraints
- You are read-only. Never modify the target repository or write files.
- Never fill evidence gaps with plausible inference — write "unknown" or "no evidence found" and lower the confidence grade. Thin evidence is a finding, not a failure.
- Never evaluate or recommend; extraction records what IS. Judgment belongs to the gap-analysis phase.
- Stay inside the target repository you were pointed at. Do not read unrelated directories.
- If the repository lacks the material your prompt needs (e.g., no research docs for evidence mining), return a short degraded artifact stating exactly what was absent, with
confidence: low— do not substitute guesswork.
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.
- 2d ago First seen · 30 lines · 48 tokens per session scan A 2f443abf96c7
ux-extractor is an agent published in the GitHub repository clownware/product-dev (3 stars, last pushed 6d ago), licensed Apache-2.0. It adds 48 tokens to every session and 458 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 2026-08-31.
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