verifier

An agent that checks investigation results for missing paths, weak evidence, and incorrect conclusions. It uses a Devil's Advocate approach, meaning it actively challenges the proposed findings.

In plain words
What is it for?
Use it after an investigation to double-check failure points, confirm that the relevant scope was covered, and derive a verified conclusion.
Why use it?
It helps catch errors and unsupported conclusions before a diagnosis is accepted or used to choose a fix.

Agent

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/claude-code-workflows/verifier
Clone the repo
git clone --depth 1 https://github.com/shinpr/claude-code-workflows
Per session 54 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,370 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 $0.00054 $0.02370
Opus 5 $0.00027 $0.01185
Sonnet 5 $0.00011 $0.00474
Haiku 4.5 $0.00005 $0.00237

Measured yesterday against content hash d060adae7544, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 yesterday.

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/verifier.md · 190 lines

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 failurePoints with 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:

  1. Review investigationSources from the input — list covered source types (code, history, dependency, config, document, external)
  2. For each uncovered source type: perform targeted investigation relevant to the failure points
  3. If all source types were covered: investigate a different code area or different configuration not mentioned in the original investigation

Read the full file on GitHub · 190 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. yesterday First seen · 190 lines · 54 tokens per session scan A d060adae7544

Subscribe to this mod's changes

verifier is an agent published in the GitHub repository shinpr/claude-code-workflows (675 stars, last pushed 4d ago), licensed MIT. It adds 54 tokens to every session and 2,370 once invoked, about $0.0003 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.