Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add pcopu/coco --skill coco-deliverygit clone --depth 1 https://github.com/pcopu/cocoWrote 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/pcopu/coco/coco-delivery)<a href="https://agentmods.dev/skills/pcopu/coco/coco-delivery"><img src="https://agentmods.dev/badge/skills/pcopu/coco/coco-delivery/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/pcopu/coco/coco-delivery"><img src="https://agentmods.dev/badge/skills/pcopu/coco/coco-delivery.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 | $0.00065 | $0.00349 |
| Opus 5.5 | $0.00026 | $0.00140 |
| Sonnet 5.5 | $0.00013 | $0.00070 |
| Haiku 4.5 | $0.00006 | $0.00035 |
Grade A, and why
coco-delivery 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.
What it actually says
CoCo Delivery Skill
Ship CoCo changes with a consistent workflow and repo-aware checks.
When to Use
Use this skill when making behavior changes in this repository, especially for:
- slash commands and callback menus
- app-server send paths
- queueing, steer, and watchdog behavior
- session/worktree lifecycle flows
- status/usage/model panels
- allowlist and approval UX
When NOT to Use
Do not use this skill for:
- unrelated Python projects
- one-off shell tasks not tied to
CoCo - docs-only edits with no bot/runtime behavior impact
Workflow
- Locate the flow entrypoints.
- Patch the smallest safe surface first (helpers before handlers).
- Add or update targeted tests.
- Run focused tests for touched areas.
- Run full test suite before finalizing.
Use references/file-map.md for file touchpoints and references/test-matrix.md for test commands.
Guardrails
- Prefer
rgfor code discovery. - Keep queue and status behavior thread/topic-safe.
- Keep queue and status behavior aligned with app-server flows.
- Add telemetry for new failure/retry branches.
- Avoid broad refactors while shipping feature requests.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 48 lines · 65 tokens per session scan A 7f75416dfb09
coco-delivery is a skill published in the GitHub repository pcopu/coco (4 stars, last pushed 10d ago), licensed MIT. It adds 65 tokens to every session and 349 once invoked, about $0.0003 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.
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