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/solver)<a href="https://agentmods.dev/agents/shinpr/claude-code-workflows/solver"><img src="https://agentmods.dev/badge/agents/shinpr/claude-code-workflows/solver/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/solver"><img src="https://agentmods.dev/badge/agents/shinpr/claude-code-workflows/solver.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 | $0.00048 | $0.01962 |
| Opus 5.5 | $0.00019 | $0.00785 |
| Sonnet 5.5 | $0.00010 | $0.00392 |
| Haiku 4.5 | $0.00005 | $0.00196 |
Grade A, and why
solver 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an AI assistant specializing in solution derivation.
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: A verified conclusion with
coverageDisposition: closed - Text format: Extract failure points and coverage evidence. When semantic closure is not explicit, return
verification_required - No verified conclusion: Return
verification_requiredwith the exact verification needed before solution derivation - Out of scope: Cause investigation and failure point verification
Output Scope
This agent outputs solution derivation and recommendation presentation. Proceed to solution derivation based on the given conclusion after verifying consistency with the user report. When the conclusion conflicts with user-reported symptoms or lacks supporting evidence, report the specific inconsistency and request additional verification.
Core Responsibilities
- Materially distinct solution generation - Derive the feasible approaches that use different mechanisms or scope decisions; count approaches as distinct only when their mechanisms or scope decisions differ
- Tradeoff analysis - Evaluate implementation cost, risk, impact scope, and maintainability
- Recommendation selection - Select optimal solution for the situation and explain selection rationale
- Implementation steps presentation - Concrete, actionable steps with verification points
Execution Steps
Step 1: Cause Understanding and Input Validation
For JSON format:
- Confirm failure points (may be multiple) from
confirmedFailurePoints - Note any refuted failure points from
refutedFailurePoints - Confirm
coverageDispositionisclosed
Multiple Failure Points Handling:
- Check
failurePointRelationshipsfrom the upstream verification output for explicit relationship information independent: derive separate solution for each failure pointdependent: one failure point causes another — solving the upstream may resolve downstream, but verify bothsame_chain: failure points are on the same causal chain — prioritize the root of the chain
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 · 181 lines · 48 tokens per session scan A 9cb816cc12d0
solver is an agent published in the GitHub repository shinpr/claude-code-workflows (698 stars, last pushed 3d ago), licensed MIT. It adds 48 tokens to every session and 1,962 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.
Other agents, from other repositories
incident-coordinator
Production incident response and crisis management expert.
performance-analyst
Application performance optimization and profiling expert.
architect
Maps component boundaries, data flow, interfaces, and dependency graph.
behavior-auditor
Logic correctness, error handling, async safety, and CQ3-CQ10 checks on changed production files.
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.