Borrowing it
Nothing to install: this file belongs to anthroos/openexp. 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/anthroos/openexp/main/CLAUDE.mdgit clone --depth 1 https://github.com/anthroos/openexpWrote 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/anthroos/openexp/claude-md)<a href="https://agentmods.dev/instructions/anthroos/openexp/claude-md"><img src="https://agentmods.dev/badge/instructions/anthroos/openexp/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/anthroos/openexp/claude-md"><img src="https://agentmods.dev/badge/instructions/anthroos/openexp/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 | $0.00784 | $0.00784 |
| Opus 5.5 | $0.00314 | $0.00314 |
| Sonnet 5.5 | $0.00157 | $0.00157 |
| Haiku 4.5 | $0.00078 | $0.00078 |
Grade A, and why
openexp 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 1mo 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenExp — Development Instructions
Memory Protocol (MANDATORY)
OpenExp gives Claude Code persistent memory: hybrid retrieval (vector + BM25), prediction-outcome feedback, and the experience-pack pipeline. For the system to learn from your work, follow this protocol every task:
Before starting any task:
search_memory("relevant context for this task")
Find prior experience, decisions, mistakes. Hooks do auto-recall on each message, but you MUST do a targeted search before complex tasks.
After completing a task:
add_memory("what was decided/done and why", type="decision")
Capture outcomes, not just actions. The prediction loop (below) cannot reward retrieval if the outcome was never written down.
When the user shares context:
add_memory("the context", type="fact")
Immediately. Don't wait. Every piece of context improves future retrieval.
Prediction loop (build judgment over time):
When you make a prediction or recommendation (deal outcome, approach success, client reaction):
log_prediction("prediction text", confidence=0.7, memory_ids=["ids-that-informed-this"])
Later, when the outcome is known:
log_outcome(prediction_id="pred_xxx", outcome="what happened", reward=0.8)
This is the active feedback path — verified outcomes flow back to the memories that informed them. Use for: deal predictions, strategy recommendations, client behavior forecasts, technical approach bets.
Architecture
Full reference: docs/storage-system.md for retrieval/scoring details, docs/experience-library.md for the Experience Library pipeline.
openexp/core/— search, scoring, lifecycle, storageopenexp/ingest/— Transcript ingest + Experience Library pipeline (chunking, topic mapping, experience extraction)openexp/mcp_server.py— MCP STDIO server (5 tools: search_memory, add_memory, log_prediction, log_outcome, memory_stats)openexp/cli.py— CLI (search, ingest, chunk, topics, stats, compact, experience, viz)scripts/batch_label.py— Batch experience labeling across all threadstests/— pytest suite (run it, don't trust counts written in docs)
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.
- 1mo ago Changed · -2 lines · -15 tokens per session 4aea14886d5c
- 1mo ago First seen · 78 lines · 799 tokens per session scan A 95ce8604737d
openexp CLAUDE.md is an instructions file published in the GitHub repository anthroos/openexp (59 stars, last pushed 1mo ago), licensed MIT. It adds 784 tokens to every session, about $0.0031 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 2026-08-30.
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).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.