CORAL is infrastructure for autonomous coding agents that run experiments on a codebase, have their work graded, share knowledge, and evolve solutions across repeated attempts. It is used for autoresearch workflows with agents such as Claude Code, OpenCode, Codex, Cursor Agent, and Kiro. The catalogue entries provide skills, agents, instructions, a plugin, and a hook for operating these workflows.
Borrowing it
Nothing to install: this file belongs to Human-Agent-Society/CORAL. 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/Human-Agent-Society/CORAL/main/CLAUDE.mdgit clone --depth 1 https://github.com/Human-Agent-Society/CORALWrote 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/human-agent-society/coral/claude-md)<a href="https://agentmods.dev/instructions/human-agent-society/coral/claude-md"><img src="https://agentmods.dev/badge/instructions/human-agent-society/coral/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/human-agent-society/coral/claude-md"><img src="https://agentmods.dev/badge/instructions/human-agent-society/coral/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 | $0.04578 | $0.04578 |
| Opus 5.5 | $0.01831 | $0.01831 |
| Sonnet 5.5 | $0.00916 | $0.00916 |
| Haiku 4.5 | $0.00458 | $0.00458 |
Grade A, and why
CORAL 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 — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CORAL
An orchestration system for autonomous coding agents — agents follow a CORAL.md guide, run experiments, share knowledge, and loop forever.
Project Overview
Core pattern: Spawn agents → agents read CORAL.md → commit changes → grader daemon scores them → repeat
Key concepts:
- Agents are the optimizers — Claude Code (or Codex / Cursor / Kiro / OpenCode) subprocesses, each in its own git worktree.
- Shared state via
.coral/— split intopublic/(visible to agents through a runtime-specific symlink like.claude/,.codex/,.opencode/) andprivate/(grader venv, hidden inputs — denied to agents). The grader's own source is surfaced read-only to agents as<shared_dir>/grader/(a symlink to the realgrader/package) so they can read how they're scored. - Async eval loop —
coral eval -m "..."stages+commits and writes a pending attempt; a long-running grader daemon picks it up, grades it inside a detached worktree, and writes the final score back. Default behavior blocks until the score lands;--no-waitreturns immediately. - CLI orchestration — 18 commands (see Commands below), grouped under
coral start / status / eval / log / ....
Directory Structure
| Directory | Purpose |
|---|---|
coral/types.py |
Core types: Task, Score, ScoreBundle, Attempt |
coral/config.py |
OmegaConf-backed YAML configuration (CoralConfig, GraderConfig, AgentConfig, GatewayConfig, WarmStartConfig, HeartbeatActionConfig, ...) |
coral/task/ |
Frontend-independent task validation with structured reports, progress events, and baseline grading |
coral/agent/ |
Agent lifecycle: manager.py (multi-agent supervisor), runtime.py (abstract), state.py, heartbeat.py, exit_classifier.py, warmstart.py, process.py, registry.py |
coral/sandbox/ |
Pluggable agent sandboxing (agents.sandbox): protocol.py (SandboxProvider + spec/context types), registry.py (name or module:Class entrypoint resolution), srt.py (built-in srt provider: OS-level FS/network enforcement + allow-all proxy) |
coral/agent/builtin/ |
Concrete runtimes: claude_code, codex, cursor_agent, kiro, opencode |
coral/grader/ |
Grader stack: protocol.py, base.py, task_grader.py, loader.py, subprocess_grader.py, daemon.py (long-running grader), builtin/function_grader.py |
coral/hub/ |
Shared state: attempts.py, notes.py, skills.py, checkpoint.py (git-tracked snapshots of .coral/public/), heartbeat.py, prompts/ (built-in heartbeat prompts) |
coral/hooks/ |
post_commit.py — implements submit_eval (called by coral eval) |
coral/workspace/ |
Run layout: project.py (run dir setup), worktree.py (per-agent git worktrees + symlinks), repo.py (clone/init), grader_env.py (.coral/private/grader_venv/) |
coral/template/ |
coral_md.py + coral.md.template / coral_single.md.template; bundled agents/ (deep-researcher, librarian) and skills/ (deep-research, organize-files, skill-creator) seeded into every run |
coral/gateway/ |
Optional LiteLLM gateway (server.py, middleware.py, config.py) for intercepting agent model traffic |
coral/web/ |
Starlette web dashboard (app.py, api.py, events.py, logs.py, static/) |
coral/cli/ |
CLI package: start.py, query.py, eval.py, heartbeat.py, agents.py (user-level bindings), ui.py, author.py, validation.py, _helpers.py |
coral/user_agents.py |
User-level agent bindings: load/save ~/.config/coral/agents.yaml, expanded into concrete agent fields by config._expand_bindings |
examples/ |
Task configs (circle_packing, swebench-verified, kernel_engineering, mnist, ...) — each is a task.yaml + seed/ + packaged grader (grader/ referenced by grader.entrypoint); hidden data is declared in grader.private (copied into .coral/private/) and must live outside the agent-visible grader/ package |
plugin/ |
Skills-first, multi-harness plugin for driving coral from another harness (Superpowers-style: one shared skills/, per-harness .claude-plugin/ + .codex-plugin/ manifests, per-harness hooks/ with a SessionStart install check). Per-harness marketplace manifests at the repo root — .claude-plugin/marketplace.json (Claude) and .agents/plugins/marketplace.json (Codex git-backed, git-subdir → ./plugin) — for owner/repo discovery. No MCP. See plugin/README.md. |
tests/ |
Pytest suite (config, grader, hooks, hub, manager reliability, daemon, workspace, ...) |
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 · 220 lines · 4,578 tokens per session scan A 588d2cc7b2cf
CORAL CLAUDE.md is an instructions file published in the GitHub repository Human-Agent-Society/CORAL (1,098 stars, last pushed 6d ago), licensed Apache-2.0. It adds 4,578 tokens to every session, about $0.0183 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).
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.