Borrowing it
Nothing to install: this file belongs to keychain-io/trustable-ai. 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/keychain-io/trustable-ai/main/CLAUDE.mdgit clone --depth 1 https://github.com/keychain-io/trustable-aiWrote 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/keychain-io/trustable-ai/claude-md)<a href="https://agentmods.dev/instructions/keychain-io/trustable-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/keychain-io/trustable-ai/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/keychain-io/trustable-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/keychain-io/trustable-ai/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 | $0.04180 | $0.04180 |
| Opus 5.5 | $0.01672 | $0.01672 |
| Sonnet 5.5 | $0.00836 | $0.00836 |
| Haiku 4.5 | $0.00418 | $0.00418 |
Grade A, and why
trustable-ai 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 2mo 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 — 476 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trustable AI Development Workbench
⚠️ CRITICAL: For AI Agents Working On This Project
VISION.md describes PROBLEMS TO SOLVE, not behaviors to emulate.
When VISION.md says "AI agents routinely claim completion without doing work" or "skip verification steps" - those are ANTI-PATTERNS this framework prevents. As an AI agent working ON this project:
- ✅ DO: Verify all work is complete before marking tasks done
- ✅ DO: Query external sources of truth (Azure DevOps, file system) to verify work exists
- ✅ DO: Follow workflow verification gates explicitly - never skip them
- ✅ DO: Implement the SOLUTIONS described in VISION.md (verification gates, state persistence)
- ❌ DO NOT: Skip verification steps described in workflow templates
- ❌ DO NOT: Claim work is complete without external verification
- ❌ DO NOT: Reproduce the anti-patterns VISION.md describes
You are building the solution to AI unreliability. Execute workflows with complete, programmatic verification.
Overview
Trustable AI is an AI-assisted software lifecycle framework that solves the fundamental unreliability of AI coding agents (VISION.md). Generic AI agents fail software development tasks by claiming completion without doing work, skipping verification steps, and losing progress when sessions crash.
This framework doesn't make AI smarter - it makes AI failures visible and recoverable through structured SDLC processes that catch errors early.
Project Overview
Trustable AI is an AI-assisted software lifecycle framework featuring multi-agent orchestration, state management, and work tracking integration. It enables reliable software development with Claude Code through specialized agents, re-entrant workflows, and hierarchical context management.
Current State (v1.2.0):
- ✅ Configuration system with Pydantic validation
- ✅ Agent template rendering with project context injection (12 agents)
- ✅ Workflow template rendering (7 workflows)
- ✅ Work tracking platform adapters (Azure DevOps, file-based, extensible to Jira/GitHub)
- ✅ CLI (
trustable-ai) for initialization, configuration, and management - ✅ State management with re-entrancy support
- ✅ Profiling and analytics
- ✅ Skills system for reusable capabilities
- ✅ Learnings capture system
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.
- 2mo ago First seen · 476 lines · 4,180 tokens per session scan A fe370ddfd32c
trustable-ai CLAUDE.md is an instructions file published in the GitHub repository keychain-io/trustable-ai (2 stars, last pushed 8mo ago), licensed MIT. It adds 4,180 tokens to every session, about $0.0167 per session on Opus 5.5. 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 2026-08-31.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.