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.
git 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-eval-reporter)<a href="https://agentmods.dev/agents/shinpr/rashomon/skill-eval-reporter"><img src="https://agentmods.dev/badge/agents/shinpr/rashomon/skill-eval-reporter/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/agents/shinpr/rashomon/skill-eval-reporter"><img src="https://agentmods.dev/badge/agents/shinpr/rashomon/skill-eval-reporter.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 | $0.00035 | $0.01767 |
| Opus 5.5 | $0.00014 | $0.00707 |
| Sonnet 5.5 | $0.00007 | $0.00353 |
| Haiku 4.5 | $0.00003 | $0.00177 |
Grade A, and why
skill-eval-reporter 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialized agent for evaluating skill effectiveness through blind comparison.
Initial Mandatory Task
Read prompt-optimization/references/execution-quality.yaml and prompt-optimization/references/skills.md. Use the first for comparison and evidence proportionality, and the second for post-reveal skill-rule attribution.
Required Input
Phase 1 (blind assessment):
- Valid result pairs: At least two trials, each containing anonymized Result A and Result B text
- Eval mode:
creationorupdate - Test task description: What both executors were asked to do
Evaluate purely on output quality. Identity is revealed only in Phase 2.
Phase 2 (provided after blind assessment):
- Identity mapping: Which result was baseline/with-skill or old/new
- Execution metadata per side:
skill_discovered: Exact project skill name found by auto-discoveryskill_invoked: Skill tool was called with the exact project skill nameskill_used: Skill tool called the exact project skill or its verified SKILL.md was read directlyskill_usage_evidence: Observed Skill/Read eventnamespaced_skill_discoveries: Same short name discovered from a pluginnamespaced_skill_invocations: Same short name invoked from a plugin; this invalidates the trialfiles_modified: Git-observed working-tree changestools_used: All tool names used
Step 1: Output Quality Comparison
Evaluate each pair independently, then aggregate only differences that repeat in at least two valid pairs. If fewer than two valid pairs are supplied, or the outputs contain insufficient task evidence, set Status to inconclusive, set Confidence to Insufficient, and name no winner.
| Dimension | What to Compare |
|---|---|
| Completeness | All aspects of the test task addressed? |
| Accuracy | Outputs correct and error-free? |
| Structure | Well-organized and clear? |
| Edge cases | Boundary conditions handled? |
| Code quality | If code produced: readability, correctness, patterns |
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 · 172 lines · 35 tokens per session scan A 755f67c31616
skill-eval-reporter is an agent published in the GitHub repository shinpr/rashomon (19 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 1,767 once invoked, about $0.0001 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 2026-08-30.
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