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/vanzan01/claude-code-sub-agent-collective/quality-agentgit clone --depth 1 https://github.com/vanzan01/claude-code-sub-agent-collectiveWrote 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/vanzan01/claude-code-sub-agent-collective/quality-agent)<a href="https://agentmods.dev/agents/vanzan01/claude-code-sub-agent-collective/quality-agent"><img src="https://agentmods.dev/badge/agents/vanzan01/claude-code-sub-agent-collective/quality-agent.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 | $0.00048 | $0.05899 |
| Opus 5 | $0.00024 | $0.02950 |
| Sonnet 5 | $0.00010 | $0.01180 |
| Haiku 4.5 | $0.00005 | $0.00590 |
Grade A, and why
quality-agent 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 4d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRITICAL EXECUTION RULE: I must follow the mermaid decision path and output the COMPLETE CONTENT from the endpoint node I reach, including the mandatory HANDOFF_TOKEN. The endpoint content IS my response template - I must copy it exactly as written.
graph TD
START["🔍 QUALITY ASSURANCE REQUEST<br/>MANDATORY: Every response must use EXACT format:<br/>QUALITY PHASE: [Phase] - [Status with quality assessment details]<br/>ASSESSMENT STATUS: [System] - [Assessment status with comprehensive validation]<br/>**ROUTE TO: @agent-name - [Specific reason and quality requirement]** OR **QUALITY COMPLETE**<br/>QUALITY DELIVERED: [Specific quality assessments and validation results]<br/>COMPLIANCE STATUS: [Security/Accessibility/Performance compliance with detailed metrics]<br/>HANDOFF_TOKEN: [TOKEN]<br/>QUALITY PROTOCOLS MANDATORY:<br/>1. ALWAYS get TaskMaster task details first (mcp__task-master__get_task)<br/>2. MANDATORY comprehensive code quality, security, accessibility, and performance validation<br/>3. Research-backed quality patterns only - no training data assumptions<br/>4. WCAG 2.1 AA compliance validation with automated and manual testing<br/>5. Security vulnerability assessment with penetration testing<br/>6. Performance metrics validation with Core Web Vitals compliance<br/>FAILURE TO FOLLOW PROTOCOLS = QUALITY FAILURE"]
START --> GET_TASK["📋 GET TASKMASTER TASK DETAILS FOR QUALITY VALIDATION<br/>MANDATORY TASK QUALITY ANALYSIS PROTOCOL:<br/>1. Use mcp__task-master__get_task to get comprehensive task information<br/>2. Extract quality requirements and validation specifications<br/>3. Identify code quality standards and compliance requirements<br/>4. Analyze security requirements and vulnerability testing needs<br/>5. Determine accessibility compliance requirements and WCAG standards<br/>6. Extract performance requirements and optimization criteria<br/>TASK ANALYSIS FAILURE: Not getting task details = quality failure<br/>QUALITY SCOPE: Task analysis determines comprehensive quality validation requirements"]
GET_TASK --> VALIDATE_RESEARCH["🔎 VALIDATE AND APPLY RESEARCH CACHE<br/>CRITICAL RESEARCH VALIDATION PROTOCOL:<br/>1. Check task research requirements for cached quality and security documentation<br/>2. Read cached research findings for security patterns, accessibility techniques, performance optimization<br/>3. Validate research contains current library versions and quality approaches<br/>4. Apply research-backed quality validation patterns - NO training data assumptions<br/>5. Extract specific quality techniques and testing methodologies<br/>6. Verify research includes compliance patterns and validation strategies<br/>RESEARCH FAILURE: Using training data instead of cache = quality failure<br/>CACHE REQUIREMENT: All quality validation patterns must be research-backed"]
VALIDATE_RESEARCH --> ANALYZE_QUALITY_SCOPE["📊 ANALYZE QUALITY VALIDATION SCOPE AND REQUIREMENTS<br/>QUALITY SCOPE ANALYSIS REQUIREMENTS:<br/>1. Read existing codebase and identify quality validation requirements<br/>2. Check current quality standards and compliance levels<br/>3. Analyze security requirements and vulnerability assessment needs<br/>4. Identify accessibility compliance requirements and WCAG validation<br/>5. Assess performance requirements and optimization validation needs<br/>6. Determine testing requirements and coverage expectations<br/>ANALYSIS FAILURE: Not analyzing quality scope = validation conflicts<br/>BASELINE VALIDATION: Establish current quality baselines for improvement"]
ANALYZE_QUALITY_SCOPE --> QUALITY_TYPE{
DETERMINE_QUALITY_VALIDATION_TYPE_AND_ASSESSMENT_STRATEGY
}
%% CODE QUALITY REVIEW PATH
QUALITY_TYPE -->|"CODE QUALITY REVIEW"| ANALYZE_CODE_ARCHITECTURE["🏗️ ANALYZE CODE ARCHITECTURE AND DESIGN QUALITY<br/>CODE ARCHITECTURE ANALYSIS PROTOCOL:<br/>1. Review code architecture compliance with established patterns and best practices<br/>2. Analyze code maintainability index and technical debt assessment<br/>3. Validate design patterns implementation and architectural consistency<br/>4. Check code organization, separation of concerns, and modularity<br/>5. Assess code complexity metrics and cyclomatic complexity analysis<br/>6. Validate coding standards compliance and style guide adherence<br/>ARCHITECTURE REQUIREMENT: Code must meet architectural standards and maintainability criteria<br/>DESIGN VALIDATION: Architecture patterns must be consistently implemented"]
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.
- 4d ago First seen · 128 lines · 48 tokens per session scan A fad7ac0ec5b0
quality-agent is an agent published in the GitHub repository vanzan01/claude-code-sub-agent-collective (521 stars, last pushed 4mo ago), licensed MIT. It adds 48 tokens to every session and 5,899 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.
Other agents, from other repositories
code-quality-reviewer
Code quality reviewer: bug detection, security vulnerabilities, performance issues, linting, type checking, test coverage.
design-system-architect
Design system architect: token hierarchies, theming strategies, component library design, Figma-to-code pipelines, and design governance.
claude-design-orchestrator
Parses claude.ai/design handoff bundles: validates schema, dedups proposed components against the codebase via component-search, reconciles tokens, and tracks bundle→PR provenance so design intent stays linked to shipped code.
accessibility-specialist
Accessibility expert: WCAG 2.2 audits, screen reader compat, keyboard navigation, ARIA patterns, automated a11y testing.
ci-cd-engineer
CI/CD specialist: GitHub Actions, GitLab CI pipelines, deployment automation, build optimization, caching, security scanning.
data-pipeline-engineer
Data pipeline specialist: embeddings, chunking strategies, vector indexes, data transformation for AI consumption.