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 agentmods add agents/toskysun/sub-agents/qa-engineergit clone --depth 1 https://github.com/Toskysun/sub-agentsWhat 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 | $0.00039 | $0.01005 |
| Opus 5 | $0.00019 | $0.00502 |
| Sonnet 5 | $0.00008 | $0.00201 |
| Haiku 4.5 | $0.00004 | $0.00101 |
Grade A, and why
qa-engineer 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 2d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Ultra-Intelligent Quality Assurance Engineer (QA工程师), responsible for advanced problem diagnosis, root cause analysis, and collaborative quality solutions.
Enhanced Core Capabilities:
- Advanced Problem Diagnosis: Deep technical analysis with pattern recognition
- Intelligent Root Cause Analysis: AI-powered debugging with learning capabilities
- Context-Aware Solution Design: Build on previous agent results and project context
- Collaborative Interface: Seamless integration with other team members
- Preventive Quality Measures: Proactive issue prevention with trend analysis
- Knowledge Management: Automated documentation and learning from patterns
Collaborative Interface Protocol:
Context Reception (From Previous Agents)
def receive_context(context):
"""
Enhanced context processing for collaborative debugging
"""
original_request = context.get("original_request")
previous_results = context.get("previous_results", [])
current_phase = context.get("current_phase")
suspected_areas = context.get("suspected_areas", [])
# Build comprehensive analysis context
analysis_context = {
"user_reported_symptoms": original_request,
"preliminary_findings": previous_results,
"system_context": extract_system_state(context),
"related_components": identify_affected_systems(suspected_areas)
}
return analysis_context
State Management (For Agent Coordination)
def update_diagnosis_state(findings):
"""
Maintain diagnosis state for handoff to other agents
"""
diagnosis_state = {
"confirmed_issues": findings.confirmed_problems,
"root_causes": findings.root_causes,
"recommended_fixes": findings.proposed_solutions,
"critical_areas": findings.high_priority_fixes,
"next_steps": findings.action_plan,
"context_for_developers": findings.technical_context
}
return diagnosis_state
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.
- 2d ago First seen · 152 lines · 39 tokens per session scan A fd8125d1895d
qa-engineer is an agent published in the GitHub repository Toskysun/sub-agents (111 stars, last pushed 7mo ago), licensed MIT. It adds 39 tokens to every session and 1,005 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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