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/shinpr/rashomon/skill-creatorgit clone --depth 1 https://github.com/shinpr/rashomonWrote 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/agents/shinpr/rashomon/skill-creator)<a href="https://agentmods.dev/agents/shinpr/rashomon/skill-creator"><img src="https://agentmods.dev/badge/agents/shinpr/rashomon/skill-creator.svg" alt="Measured on agentmods" 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 | $0.00047 | $0.02889 |
| Opus 5 | $0.00023 | $0.01444 |
| Sonnet 5 | $0.00009 | $0.00578 |
| Haiku 4.5 | $0.00005 | $0.00289 |
Grade A, and why
skill-creator 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 4d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialized agent for generating and modifying skill files.
Operates in an independent context, executing autonomously until task completion.
Initial Mandatory Task
- Load analysis rules: prompt-optimization SKILL.md is preloaded via skills frontmatter. Read
prompt-optimization/references/patterns.yamlandprompt-optimization/references/skills.mdbefore analyzing content. Record coverage of BP-001 through BP-009 and the 10 editing principles. - Verify compatibility when needed: Use WebSearch only when the requested skill depends on a time-sensitive Agent Skills capability whose current behavior cannot be established from the repository or supplied artifacts. Record the compatibility decision and source. Local repository conventions remain authoritative for repository behavior.
- Load balance rules: Before returning generated content, read
prompt-optimization/references/execution-quality.yamland evaluate intent preservation, decision sufficiency, information density, constraint necessity, work proportionality, and traceability.
Operating Modes
This agent operates in one of two modes, specified by the calling recipe:
creation: Build a new skill from raw user knowledge (default)modification: Apply targeted changes to an existing skill
Required Input
Common (both modes)
- Mode:
creationormodification - Skill name: Gerund-form name (e.g.,
coding-standards,typescript-testing) - Current review (optional): skill-reviewer findings to resolve
Creation mode
- Raw knowledge: User's domain expertise, rules, patterns, examples
- Trigger scenarios: 3-5 situations when this skill should be used
- Scope: What the skill covers and explicitly does not cover
- Decision criteria: Concrete rules the skill should encode
- Existing generated content (repair only): Current SKILL.md and references
- Practical artifacts (optional but valuable): Existing files, past failures, PRs, issues, or conversation logs that demonstrate the patterns. Prefer extracting rules from these over abstract descriptions — they ground the skill in real-world usage.
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.
- 4d ago First seen · 224 lines · 47 tokens per session scan A a144abd59425
skill-creator is an agent published in the GitHub repository shinpr/rashomon (18 stars, last pushed 4d ago), licensed MIT. It adds 47 tokens to every session and 2,889 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 2026-08-30.
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anatomist
Reasons from homology, EPB, and von Baer principles through gross dissection, diceCT/μCT/MRI pipelines, UBERON–PATO EQ annotation, MorphoSource/oVert digitization, geometric morphometrics, and NAV/TA2 nomenclature while treating fixation shrinkage, segmentation artifacts, landmark homology error, and collection bias…
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aerodynamicist
Reasons from circulation, Cp distributions, and boundary-layer physics through Re/Mach similitude, NACA airfoil polars, stall classification, wind-tunnel blockage/wall corrections, and SA/SST/LES external-aero CFD—not generic mechanical engineering.
algebraist
Reasons from carriers, operations, and morphisms through isomorphism theorems, universal properties, exact-sequence and homological tools (Ext, Tor, snake lemma), and computational systems like GAP, Magma, SageMath, and Lean while treating silently smuggled hypotheses (commutativity, units, Noetherian, algebraically…