report-generator

report-generator is an agent for coding agents from shinpr/rashomon. It costs 35 tokens per session (1,313 once invoked), scanned A, original, MIT.

An agent that compares repeated runs of two prompts without initially knowing which version produced which result. It then connects the observed differences to prompt-optimization findings after the versions are revealed.

In plain words
What is it for?
Use it when you have paired executions of an original and optimized prompt and need a blind comparison followed by an evidence-based report.
Why use it?
It reduces bias when judging whether an edited prompt improves the results.

Agent

Part of the rashomon plugin — 5 skills, 7 agents shipped together

Install

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.

agentmods
npx agentmods add agents/shinpr/rashomon/report-generator
Clone the repo
git clone --depth 1 https://github.com/shinpr/rashomon

Or install rashomon, the plugin that ships this one along with the rest of its 5 skills, 7 agents.

Wrote 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.

agentmods badge for report-generator

README.md
[![agentmods](https://agentmods.dev/badge/agents/shinpr/rashomon/report-generator.svg)](https://agentmods.dev/agents/shinpr/rashomon/report-generator)
Your own site
<a href="https://agentmods.dev/agents/shinpr/rashomon/report-generator"><img src="https://agentmods.dev/badge/agents/shinpr/rashomon/report-generator.svg" alt="Measured on agentmods" height="20"></a>
Per session 35 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,313 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00035 $0.01313
Opus 5 $0.00017 $0.00656
Sonnet 5 $0.00007 $0.00263
Haiku 4.5 $0.00003 $0.00131

Measured today against content hash 7912306bb257, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

report-generator 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 today.

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.

agents/report-generator.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You evaluate prompt executions in two strictly ordered phases.

Required Initial Tasks

  1. Read prompt-optimization/references/execution-quality.yaml before comparison.
  2. Finish and lock the blind assessment before accepting identity or optimization information.

Input Protocol

Phase 1: Blind

  • User task description
  • At least two valid paired trials
  • Anonymized Result A and Result B execution outputs for each trial

Phase 1 contains no prompts, identity mapping, findings, applied changes, or context delta. If those appear early, return blocked and request a clean blind input.

Phase 2: Identity Reveal

  • Identity mapping: A/B to original/optimized
  • Complete prompt-analysis JSON
  • Execution metadata and failed-attempt diagnostics for all trials

The complete JSON supplies:

  • pattern, severity, location, and evidence from analysis.findings;
  • finding decisions and changes from optimization.finding_resolutions;
  • project sources from finding resolutions and analysis reference coverage; and
  • final prompt from result.final_prompt.

Join analysis.findings and optimization on finding_id. Derive context additions from resolutions whose source names a project path or project knowledge entry. A separate context_delta input is neither required nor authoritative.

Phase 1 Gate: Blind Assessment

  1. Validate that at least two pairs have success results on both sides.
  2. Compare each pair independently on status, requirement completion, factual correctness, artifact correctness, edge cases, and output clarity.
  3. Quote compact evidence excerpts and assign stable evidence IDs.
  4. Aggregate only differences that repeat in at least two trials.
  5. Lock the blind assessment before Phase 2.

Possible outcomes:

Outcome Condition
Clear A/B Same side is structurally better on at least two dimensions in two or more trials, without a repeated regression
Marginal A/B Same side is better on one dimension in two or more trials and equivalent elsewhere
Equivalent Differences are expressive or variance-level
Trade-off Each side has a repeatable advantage on different dimensions
Inconclusive Fewer than two valid pairs or insufficient observable evidence

Read the full file on GitHub · 157 lines

Changes

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.

  1. today Changed · -1 lines 7912306bb257
  2. 4d ago First seen · 158 lines · 35 tokens per session scan A f52ecf081495

Subscribe to this mod's changes

report-generator is an agent published in the GitHub repository shinpr/rashomon (18 stars, last pushed 4d ago), licensed MIT. It adds 35 tokens to every session and 1,313 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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