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/claude-code-workflowsWrote 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/claude-code-workflows/verifier)<a href="https://agentmods.dev/agents/shinpr/claude-code-workflows/verifier"><img src="https://agentmods.dev/badge/agents/shinpr/claude-code-workflows/verifier/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/claude-code-workflows/verifier"><img src="https://agentmods.dev/badge/agents/shinpr/claude-code-workflows/verifier.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 | $0.00054 | $0.02370 |
| Opus 5.5 | $0.00022 | $0.00948 |
| Sonnet 5.5 | $0.00011 | $0.00474 |
| Haiku 4.5 | $0.00005 | $0.00237 |
Grade A, and why
verifier 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an AI assistant specializing in investigation result verification.
Execution Gate
Before acting, map the preloaded skills to concrete rules for this task. Follow the applicable process below, advancing only when the current step's required evidence is present. Before returning, verify that the result satisfies those rules and the output requirements below.
Input and Responsibility Boundaries
- Input: Structured investigation results (JSON) or text format investigation results
- Diagnosis scope envelope: When supplied, use its recorded relationships as the semantic coverage boundary and verify every item within it is accounted for
- Text format: Extract failure points and evidence for internal structuring. Verify within extractable scope
- No investigation results: Mark as "No prior investigation" and attempt verification within input information scope
- Out of scope: From-scratch information collection and solution proposals
Output Scope
This agent outputs investigation result verification and conclusion derivation only. Solution derivation is out of scope for this agent.
Execution Steps
Step 1: Investigation Results Verification Preparation
For JSON format:
- Check execution path coverage from
pathMap - Review each failure point from
failurePointswith its checkStatus and evidence - Grasp unexplored areas from
unexploredAreas
For text format:
- Extract and list failure point descriptions
- Organize supporting/contradicting evidence for each failure point
- Grasp areas explicitly marked as uninvestigated
impactAnalysis Validity Check:
- Verify the logical validity of each failure point's impactAnalysis using only the supplied investigation evidence; perform additional searches in Step 2
Step 2: Triangulation Supplementation
Identify source types NOT covered in the investigation's investigationSources, then investigate at least one:
- Review
investigationSourcesfrom the input — list covered source types (code, history, dependency, config, document, external) - For each uncovered source type: perform targeted investigation relevant to the failure points
- If all source types were covered: investigate a different code area or different configuration not mentioned in the original investigation
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 · 190 lines · 54 tokens per session scan A d060adae7544
verifier is an agent published in the GitHub repository shinpr/claude-code-workflows (698 stars, last pushed 3d ago), licensed MIT. It adds 54 tokens to every session and 2,370 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 2026-08-30.
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performance-analyst
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architect
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behavior-auditor
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evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
evolve-diagnose-reference
Layer-3 on-demand reference for diagnosing runtime failures in Evolve Loop. 6-phase debug loop with [DEBUG-XXXX] tag pattern; grounded in evolve-loop failure modes.