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.
npx skills add joinwell52-AI/CodeFlowMu-open --skill qa-reproduce-issuegit clone --depth 1 https://github.com/joinwell52-AI/CodeFlowMu-openWrote 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/skills/joinwell52-ai/codeflowmu-open/qa-reproduce-issue)<a href="https://agentmods.dev/skills/joinwell52-ai/codeflowmu-open/qa-reproduce-issue"><img src="https://agentmods.dev/badge/skills/joinwell52-ai/codeflowmu-open/qa-reproduce-issue/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/skills/joinwell52-ai/codeflowmu-open/qa-reproduce-issue"><img src="https://agentmods.dev/badge/skills/joinwell52-ai/codeflowmu-open/qa-reproduce-issue.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 | $0.00039 | $0.00172 |
| Opus 5 | $0.00019 | $0.00086 |
| Sonnet 5 | $0.00008 | $0.00034 |
| Haiku 4.5 | $0.00004 | $0.00017 |
Grade A, and why
qa-reproduce-issue 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 10d 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.
What it actually says
QA Reproduce Issue
When to use
Use before diagnosing or verifying a bug report.
Rules
- Record environment and steps.
- Separate actual and expected results.
- Attach concise evidence.
- State reproducibility.
Required output
Use docs/skills/qa-playbook/reproduce-issue.md.
Forbidden actions
- Do not mark fixed from code inspection alone.
- Do not invent reproduction.
- Do not move lifecycle state.
Minimal example
Reproducibility: always
Step: click publish task twice
Actual: two TASK files
Expected: one TASK file
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.
- 10d ago First seen · 37 lines · 39 tokens per session scan A 4740ad341eae
qa-reproduce-issue is a skill published in the GitHub repository joinwell52-AI/CodeFlowMu-open (2 stars, last pushed 16d ago), licensed MIT. It adds 39 tokens to every session and 172 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 2026-08-31.
Other skills, from other repositories
systemic-issue-triage
Trigger: new issue, bug report, triage, backlog, issue flood, community report, root cause, dead-end, blocked user. Attack issues by root class, never one-by-one; fixes must shrink the system, not grow it.
issue-root-resolution
Trigger: root audit, atacar la raíz, issue roots, backlog roots, mechanism map, deletion-driven fix, resolver issues de raíz, close outdated issues. Audit and resolve issue clusters by verified root cause.
rdd-defect-workflow
Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide work.
post-mortem
Diagnose instruction defects and optionally submit Rosetta GitHub issue.
ijfw-debug
Root-cause analysis with hypothesis tracking. Trigger: 'debug', 'broken', 'not working', 'fix this bug', /debug.
qa-knowledge
To run QA engineering — requirements/gap analysis, scenario & spec design, test implementation, failure triage — over the QA knowledge base.