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 skullninja/coco-workflow --skill executegit clone --depth 1 https://github.com/skullninja/coco-workflowWrote 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/skullninja/coco-workflow/execute)<a href="https://agentmods.dev/skills/skullninja/coco-workflow/execute"><img src="https://agentmods.dev/badge/skills/skullninja/coco-workflow/execute/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/skullninja/coco-workflow/execute"><img src="https://agentmods.dev/badge/skills/skullninja/coco-workflow/execute.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 | $0.00039 | $0.00366 |
| Opus 5.5 | $0.00016 | $0.00146 |
| Sonnet 5.5 | $0.00008 | $0.00073 |
| Haiku 4.5 | $0.00004 | $0.00037 |
Grade A, and why
execute 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 Execute Skill
This skill delegates to the /coco:execute command, which implements the full 15-step TDD execution loop with PR workflow, AI code review, and issue tracker bridge sync.
When to Use
- Implementing a feature that has been imported into the coco tracker as an epic
- Executing tasks from a
specs/{feature}/tasks.mdthat has been converted to tracked tasks - Any multi-session work where dependency tracking matters
Alternatives
- For single-issue hotfixes or quick changes, use the
hotfixskill instead - For autonomous execution until epic completion, use
/coco:loop
Execution
Run the /coco:execute command. It handles:
- Pre-execution gate (tracker + issue tracker verification)
- Dependency-aware task selection via
coco-tracker ready - Issue branch creation (if
pr.enabled) - Issue tracker bridge (start: "In Progress")
- TDD implementation (RED -> GREEN -> verify)
- Pre-commit validation (UI change detection)
- Commit with issue key traceability
- PR creation with issue ID (if
pr.enabled) - AI code review via
code-revieweragent - Review-fix loop (max 3 iterations)
- PR merge (if
pr.enabled) - Tracker task close
- Issue tracker bridge (complete: "Done" at PR merge)
- Acceptance criteria verification
- Next task check (loop or report completion)
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 · 40 lines · 39 tokens per session scan A 552e492c18e7
execute is a skill published in the GitHub repository skullninja/coco-workflow (8 stars, last pushed 4d ago), licensed MIT. It adds 39 tokens to every session and 366 once invoked, about $0.0002 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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