quality-auditor

quality-auditor is an agent for Claude Code from rjmurillo/ai-agents. It costs 103 tokens per session (899 once invoked), scanned A, original, MIT.

An agent that scans parts of a product or code repository and grades their quality, coverage, and unresolved gaps.

In plain words
What is it for?
Use it for repository-wide or focused audits covering agents, skills, scripts, tests, documentation, workflows, scores, gaps, and trends.
Why use it?
It turns a broad quality review into scored findings that show where attention is needed and whether things are improving.

Agent for Claude Code

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the project-toolkit plugin — 95 skills, 26 commands, 33 agents, 4 hooks shipped together

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/rjmurillo/ai-agents/quality-auditor
Clone the repo
git clone --depth 1 https://github.com/rjmurillo/ai-agents

Made for: Claude Code.

Or install project-toolkit, the plugin that ships this one along with the rest of its 95 skills, 26 commands, 33 agents, 4 hooks.

Wrote 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.

agentmods badge for quality-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/rjmurillo/ai-agents/quality-auditor.svg)](https://agentmods.dev/agents/rjmurillo/ai-agents/quality-auditor)
Your own site
<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>
Per session 103 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 899 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 $0.00103 $0.00899
Opus 5 $0.00051 $0.00449
Sonnet 5 $0.00021 $0.00180
Haiku 4.5 $0.00010 $0.00090

Measured today against content hash f7454525df4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

.claude/agents/quality-auditor.md · 100 lines

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 memory
    • serena/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

Read the full file on GitHub · 100 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. today Changed f7454525df4a
  2. 5d ago First seen · 100 lines · 103 tokens per session scan A e1001a491727

Subscribe to this mod's changes

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.