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/skills/coral-extend/SKILL.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/skills/human-agent-society/coral/coral-extend)<a href="https://agentmods.dev/skills/human-agent-society/coral/coral-extend"><img src="https://agentmods.dev/badge/skills/human-agent-society/coral/coral-extend/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/skills/human-agent-society/coral/coral-extend"><img src="https://agentmods.dev/badge/skills/human-agent-society/coral/coral-extend.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00152 | $0.01616 |
| Opus 5 | $0.00076 | $0.00808 |
| Sonnet 5 | $0.00030 | $0.00323 |
| Haiku 4.5 | $0.00015 | $0.00162 |
Grade A, and why
coral-extend 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 12d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extending the CORAL framework
For day-to-day debug / reproduce loops see the sibling coral-debug skill. For creating a new examples/<task>/ (seed + task.yaml + grader package) see coral-new-task. This skill covers adding new components to the CORAL package itself.
Extending the grader infrastructure
If you're writing a grader for a specific task, use coral-new-task. This section is only for changes to the grader framework under coral/grader/:
- New helpers on
TaskGrader(coral/grader/task_grader.py) — make sure they're useful to multiple existing example graders before adding. - New
GraderInterfaceimplementations (coral/grader/protocol.py/base.py) — the bar is high; the existing protocol covers everything we currently need. - Daemon-side changes (
coral/grader/daemon.py) — concurrency, queue caps, worktree isolation, retry policy. Cover withtests/test_grader_daemon.py. - Built-in graders under
coral/grader/builtin/—function_grader.pyis the only one today; not wired throughtask.yaml. New built-ins should justify why aTaskGradersubclass per task isn't enough.
A new agent runtime
Adding a new runtime (e.g. another coding-agent CLI) means three small files plus a registry entry.
- Create
coral/agent/builtin/<name>.pyand subclassAgentRuntime(coral/agent/runtime.py). Existing runtimes are the canonical reference —claude_code.pyis the most complete;codex.pyandcursor_agent.pyare smaller and easier to mimic. - Register the runtime in
coral/agent/registry.py:_RUNTIMES["my_runtime"] = MyRuntime _ALIASES["mine"] = "my_runtime" _DEFAULT_MODELS["my_runtime"] = "default-model-id" - Decide the runtime's native shared-state directory name (
.claudefor Claude Code,.codexfor Codex, etc.). The worktree symlink uses this; pass it throughshared_dirsogenerate_coral_md(...)renders the right paths. - If the runtime needs special config plumbing (e.g.
cursor_agent.json,opencode.json, gateway port), follow theopencodepattern: emit a per-agent config file inside the worktree at startup. - Add a smoke test in
tests/test_<runtime>.pymodeled ontests/test_cursor_agent.py.
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.
- 12d ago First seen · 86 lines · 152 tokens per session scan A 572fc0139500
coral-extend is a skill published in the GitHub repository Human-Agent-Society/CORAL (972 stars, last pushed 3d ago), licensed Apache-2.0. It adds 152 tokens to every session and 1,616 once invoked, about $0.0008 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.
Other skills, from other repositories
cw-gates
Use before claiming any Codewhale change is done, green, or ready to land: the focused-to-broad verification ladder, the budget checks CI enforces, and the rules for what counts as a passing test.
writing
A writing guide for turning verified facts and calculations into finished text for a specific audience. It follows the requested language, structure, and length.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
interview
Ask one useful structured question at a time only when material product/implementation choices are genuinely missing; remember answers and produce a brief/spec. Discoverable facts should be investigated instead of asked.
verify
Exercise the real app/API/CLI and collect observable evidence; tests alone do not count as end-to-end verification.
new-app
Scaffold a new Atomic Agents project from scratch — create the directory, pyproject.toml, env file, first agent, and a runnable entry point. Use when the user asks to start a new atomic-agents project from scratch, says "scaffold" / "new project" / "start from zero", or runs /atomic-agents:new-app.