Borrowing it
Nothing to install: this file belongs to ankitkr3/compounded. 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/ankitkr3/compounded/main/CLAUDE.mdgit clone --depth 1 https://github.com/ankitkr3/compoundedWrote 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/ankitkr3/compounded/claude-md)<a href="https://agentmods.dev/instructions/ankitkr3/compounded/claude-md"><img src="https://agentmods.dev/badge/instructions/ankitkr3/compounded/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/ankitkr3/compounded/claude-md"><img src="https://agentmods.dev/badge/instructions/ankitkr3/compounded/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 | $0.01314 | $0.01314 |
| Opus 5.5 | $0.00526 | $0.00526 |
| Sonnet 5.5 | $0.00263 | $0.00263 |
| Haiku 4.5 | $0.00131 | $0.00131 |
Grade A, and why
compounded 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md (compounded repository)
This file is read by Claude Code when working inside this repo. It describes the codebase, conventions, and what to do (and not do) when proposing changes.
What this repo is
compounded is a Claude Code plugin that adds a trust gradient and verified skills on top of Claude's native memory primitives. The plugin layout follows the Claude Code plugin spec:
.claude-plugin/plugin.json— manifestskills/<name>/SKILL.md— built-in skills (5 of them)commands/<name>.md— slash commands (9 of them)agents/<name>.md— subagent definitions (1)hooks/hooks.json— lifecycle hooks (SessionStart, Stop, SessionEnd)scripts/*.py— Python implementation (no runtime deps; stdlib only)tests/— unittest suite
Conventions
- Python is stdlib-only. No third-party imports. compounded must not pull in dependencies for its core path. We pay this cost gladly to keep install friction at zero.
- Hooks must never fail loudly. A SessionStart or Stop hook that crashes the user's session is a P0 bug. Wrap in try/except and emit
{"continue": true, "suppressOutput": true}on any unexpected failure. See the bottom ofscripts/memory_inject.pyfor the pattern. - All paths go through
_lib.py. Don't hardcode paths in individual scripts. Add them to_lib.pyso they respectCOMPOUNDED_HOME. - All trust state changes log an event. Every promotion, demotion, verification, rejection, and use must call
log_event(). The event log is how the user audits the system. - No LLM calls from scripts. The scripts are deterministic Python. The only LLM call is the verifier subagent, which is dispatched through Claude Code's native agent system (not a direct API call).
How the lifecycle works
-
SessionStart hook (
memory_inject.py) — reads USER.md, injects it asadditionalContext. Runs in <100ms typically. -
During the session — the agent may invoke
skill_propose.py(via Bash) when it wants to save a procedure. The script validates frontmatter, runs a security scan, writes to.proposed/<name>/, and records to the trust DB.
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 First seen · 102 lines · 1,314 tokens per session scan A d031f0b71adf
compounded CLAUDE.md is an instructions file published in the GitHub repository ankitkr3/compounded (5 stars, last pushed 3mo ago), licensed MIT. It adds 1,314 tokens to every session, about $0.0053 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.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.
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).