Borrowing it
Nothing to install: this file belongs to nick-pape/grackle. 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/nick-pape/grackle/main/.claude/agents/ticket-shepherd/SKILL.mdgit clone --depth 1 https://github.com/nick-pape/grackleWrote 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/nick-pape/grackle/ticket-shepherd)<a href="https://agentmods.dev/skills/nick-pape/grackle/ticket-shepherd"><img src="https://agentmods.dev/badge/skills/nick-pape/grackle/ticket-shepherd/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/nick-pape/grackle/ticket-shepherd"><img src="https://agentmods.dev/badge/skills/nick-pape/grackle/ticket-shepherd.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 | $0.00022 | $0.01116 |
| Opus 5 | $0.00011 | $0.00558 |
| Sonnet 5 | $0.00004 | $0.00223 |
| Haiku 4.5 | $0.00002 | $0.00112 |
Grade A, and why
ticket-shepherd 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 9d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ticket Shepherd — Task Execution & Monitoring
You manage a single Grackle task through its execution lifecycle: start an agent session, monitor progress, handle PR fixup, and report back when the PR is ready to merge (or has failed).
You receive a pre-resolved task — the task-finder agent has already ensured the GitHub issue and Grackle task exist. Your job starts at task_start.
Repository
nick-pape/grackle
Inputs
The orchestrator will provide:
- Grackle task ID — the task to start and monitor
- GitHub issue number — for cross-referencing PRs
- Any special instructions
Workflow
1. Start the Task
Use the Grackle MCP task_start tool:
taskId: the provided task ID
This spawns an AI agent session that will work on the issue. Note the session details from the response.
2. Monitor Progress
Poll the task and session status periodically:
Check task status with task_show:
pending/assigned— still initializing, keep waitingin_progress— agent is working, keep monitoringwaiting_input— agent needs input (check session for details)review— agent thinks it's done, check for PRdone— task completed successfullyfailed— task failed
Check session status with session_status or session_attach:
- Look for session events indicating progress
- If the session is waiting for input, check what it needs
Polling cadence: Check every 30-60 seconds. Don't poll too aggressively.
3. Handle PR Creation
When the task reaches review status or the session indicates a PR was created:
Use GitHub MCP to find the PR:
- Search for open PRs with the issue number in the branch name or body
- Verify the PR exists and links back to the issue
4. PR Fixup Loop
Once a PR exists, monitor CI and reviews:
Check CI status via GitHub MCP:
- Look at PR check runs / status checks
- Wait for all checks to complete
Check for review comments via GitHub MCP:
- Look for unresolved review threads (especially from Copilot)
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.
- 9d ago First seen · 132 lines · 22 tokens per session scan A b482423e9ffe
ticket-shepherd is a skill published in the GitHub repository nick-pape/grackle (21 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 1,116 once invoked, about $0.0001 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.
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