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 desplega-ai/agent-swarm --skill close-issuegit clone --depth 1 https://github.com/desplega-ai/agent-swarmWrote 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/desplega-ai/agent-swarm/close-issue)<a href="https://agentmods.dev/skills/desplega-ai/agent-swarm/close-issue"><img src="https://agentmods.dev/badge/skills/desplega-ai/agent-swarm/close-issue/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/desplega-ai/agent-swarm/close-issue"><img src="https://agentmods.dev/badge/skills/desplega-ai/agent-swarm/close-issue.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 | $0.00016 | $0.00339 |
| Opus 5 | $0.00008 | $0.00169 |
| Sonnet 5 | $0.00003 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
close-issue 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.
What it actually says
Close Issue
Close a GitHub or GitLab issue with an appropriate closing comment summarizing the resolution.
Provider detection: Check the URL or remote to determine the VCS provider:
- If GitHub → use
gh issue close/gh issue comment - If GitLab → use
glab issue close/glab issue note
Arguments
issue-number-or-url: Either an issue number (e.g.,123) or a full issue URL
Workflow
- Parse the input — if given a URL, extract owner, repo, and issue number. If just a number, use the current repo context.
- Ensure repo is cloned to
/workspace/personal/<repo-name>(clone withgh repo cloneif needed). - Get issue details — read the issue title, body, comments, and check for related PRs.
- Generate closing comment — summarize what was done, reference related PRs/commits, note any follow-ups.
- Post comment and close:
gh issue close <issue-number> --comment "Your closing comment" --reason completed
Closing Reasons
completed— The issue was resolvednot_planned— Won't fix / out of scope / duplicate
Tips
- Always explain why the issue is being closed
- Reference specific PRs or commits when applicable
- If closing as "not planned", explain the reasoning
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 · 39 lines · 16 tokens per session scan A be8a380320f4
close-issue is a skill published in the GitHub repository desplega-ai/agent-swarm (754 stars, last pushed today), licensed MIT. It adds 16 tokens to every session and 339 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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