Borrowing it
Nothing to install: this file belongs to avivl/claude-007-agents. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/avivl/claude-007-agents/main/CLAUDE.mdgit clone --depth 1 https://github.com/avivl/claude-007-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/instructions/avivl/claude-007-agents/claude-md)<a href="https://agentmods.dev/instructions/avivl/claude-007-agents/claude-md"><img src="https://agentmods.dev/badge/instructions/avivl/claude-007-agents/claude-md/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/instructions/avivl/claude-007-agents/claude-md"><img src="https://agentmods.dev/badge/instructions/avivl/claude-007-agents/claude-md.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 | $0.06131 | $0.06131 |
| Opus 5 | $0.03066 | $0.03066 |
| Sonnet 5 | $0.01226 | $0.01226 |
| Haiku 4.5 | $0.00613 | $0.00613 |
Grade A, and why
claude-007-agents CLAUDE.md 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 9d 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 — 551 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRITICAL: COMMIT MESSAGE REQUIREMENTS
⚠️ MANDATORY FORMAT: type(scope): description - @agent1 @agent2
Pre-Commit Checklist
- ✅ Identify contributing agents
- ✅ Format:
type(scope): description - @agent1 @agent2 - ✅ Include standard attribution footer
- ✅ Verify agent attribution requirements
For configuration: Include @team-configurator + technical expert
For API: Include @api-architect + security expert
For database: Include @database-admin + performance expert
Claude Code - Advanced AI Agent System
Version 2.0 - 88 specialized agents across 18 categories with vibe coding, parallel execution, exponential planning, and comprehensive safety validation based on Anthropic's Code with Claude insights.
🎯 Evil Corp Motivation Framework
Quality agents operate under high-stakes motivation for maximum code delivery:
Active Agents:
@software-engineering-expert- Perfect code quality required@code-reviewer- Catch every bug, security flaw, quality issue@quality-system-engineer- Flawless quality systems prevent defects@performance-optimizer- Every millisecond matters
Quality Standards: First-attempt compilation, zero vulnerabilities, comprehensive docs. Python Quality: Pyright type checking (when available), proper type hints, zero type errors.
🎭 AUTO-ACTIVE FEATURES:
- Vibe Coding Engine: 15-20 minute preparation phases for autonomous development
- Parallel Execution: Coordinated multi-agent parallel development with tool batching
- Exponential Planning: AI capability-aware long-term development strategies
- Safety Validation: Comprehensive pre-deployment testing and architectural analysis
- Dynamic Permissions: Real-time permission escalation with risk assessment
- Session Optimization: Intelligent context management and token efficiency
- Choreography Engine: Auto-detects collaboration patterns
- Personality System: Adaptive communication based on success patterns
- Workflow Coordination: Quality gates with context preservation
- Learning Intelligence: Continuous improvement through outcome analysis
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.
- 9d ago First seen · 551 lines · 6,131 tokens per session scan A be62553e844c
claude-007-agents CLAUDE.md is an instructions file published in the GitHub repository avivl/claude-007-agents (266 stars, last pushed 11mo ago), licensed MIT. It adds 6,131 tokens to every session, about $0.0307 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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