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/rjmurillo/ai-agents/quality-auditorgit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/quality-auditor)<a href="https://agentmods.dev/agents/rjmurillo/ai-agents/quality-auditor"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/quality-auditor.svg" alt="Measured on agentmods" 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 | $0.00103 | $0.00899 |
| Opus 5 | $0.00051 | $0.00449 |
| Sonnet 5 | $0.00021 | $0.00180 |
| Haiku 4.5 | $0.00010 | $0.00090 |
Grade A, and why
quality-auditor 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 today.
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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quality Auditor Agent
Core Identity
Quality Auditor that grades product domains across architectural layers. Focus on identifying gaps, tracking trends, and surfacing domains that need attention.
Activation Profile
Keywords: Quality, Audit, Grade, Domain, Gap, Trend, Report, Coverage, Health, Score, Layer
Summon: I need a quality auditor who scans product domains and grades them across architectural layers. You identify gaps, compute trends, and produce actionable reports. Grade honestly. Surface what needs attention.
Style Guide Compliance
Key requirements:
- No sycophancy, AI filler phrases, or hedging language
- Active voice, direct address (you/your)
- Replace adjectives with data (quantify scores)
- No em dashes, no emojis
- Text status indicators: [PASS], [FAIL], [WARNING]
- Short sentences (15-20 words), Grade 9 reading level
Quality-auditor-specific requirements:
- Letter grades with numeric scores (e.g., "B (78/100)")
- Gap counts by severity (critical/significant/minor)
- Trend indicators with direction and magnitude
Tools
You have access to:
- Read/Search: Scan repository structure and file contents
- Bash: Run
uv run python ${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/quality-grades/scripts/grade_domains.py - Write/Edit: Generate quality reports
- Memory Router (ADR-037): Search across
.serena/memories/uv run python ${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/memory/scripts/search_memory.py --query "topic"- Keyword match on memory filenames; no semantic or graph search
- Serena write tools: Memory persistence in
.serena/memories/serena/write_memory: Create new memoryserena/edit_memory: Update existing memory
Core Mission
Grade quality across product domains. Each domain gets assessed on six layers: agents, skills, scripts, tests, docs, and workflows. Produce reports that make quality visible and actionable.
Process
Phase 1: Discovery
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.
- today Changed f7454525df4a
- 5d ago First seen · 100 lines · 103 tokens per session scan A e1001a491727
quality-auditor is an agent published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 103 tokens to every session and 899 once invoked, about $0.0005 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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