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Agent skill

Closing Issues

by oaustegard in oaustegard/claude-skills

Close a GitHub issue with a synthesis comment as a flowing graph — validate the synthesis, post the closing comment, close, then run a pluggable callback (e.g.

MITAuto-check passed

Install Closing Issues

skills CLI
$ npx skills add oaustegard/claude-skills --skill closing-issues -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install oaustegard/claude-skills closing-issues --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/closing-issues .claude/skills/closing-issues && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
closing-issues
GitHub stars
150
Token cost
~1.1k tokens
SKILL.md length
329 words
Files
4 (incl. scripts)
Skills in repo
69
Repo updated
First seen
Licence
MIT

At a glance

Close a GitHub issue with a synthesis comment as a flowing graph — validate the synthesis, post the closing comment, close, then run a pluggable callback (e.g.

  • Closing an issue should also capture the LEARNING (not just the diff log) and when the post-close work shouldnt block the close ack
  • SKILL.md covers Why a synthesis, not a "done"…, Internal shape, Pluggable post-close callback and Result shape, plus 3 more sections
  • Runs Python scripts from its folder; calls gh; reaches github.com; needs GH_TOKEN and GITHUB_TOKEN

What it does

Closing Issues is an agent skill from oaustegard/claude-skills. Close a GitHub issue with a synthesis comment as a flowing graph — validate the synthesis, post the closing comment, close, then run a pluggable callback (e.g. memory store) detached. Use when closing an issue should also capture the LEARNING (not just the diff log) and when the post-close work shouldn't block the close ack.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `CHANGELOG.md`, `scripts/closing_issues.py` and `tests/test_closing_issues.py`).

It works with GitHub. The repository describes itself as: My collection of Claude skills. The licence is MIT.

When your agent uses it

  • Closing an issue should also capture the LEARNING (not just the diff log) and when the post-close work shouldnt block the close ack

Example prompts

  • “/closing-issues”

Requirements

  • Python 3
  • A credential in GITHUB_TOKEN

What it can do on your machine

Read from SKILL.md and the folder at commit 6fc82b8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • gh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GH_TOKEN
    • GITHUB_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Closing Issues loads about 1.1k tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 329 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from oaustegard/claude-skills at commit 6fc82b8, republished under its MIT licence (© oaustegard). 329 words, ~1,069 tokens.

Download SKILL.mdSave it as .claude/skills/closing-issues/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
closing-issues
description
Close a GitHub issue with a synthesis comment as a flowing graph — validate the synthesis, post the closing comment, close, then run a pluggable callback (e.g. memory store) detached. Use when closing an issue should also capture the LEARNING (not just the diff log) and when the post-close work shouldn't block the close ack.
metadata.version
0.1.0
metadata.requires
flowing

Closing Issues

A flowing graph that turns "close GitHub issue + capture what I learned" into a structural DAG. The synthesis text is validated upfront, the close happens against the GitHub API, and an optional post-close callback runs detached so the close ack is unblocked.

python
from closing_issues import close_issue

result = close_issue(
    repo="owner/repo",
    number=42,
    synthesis=(
        "Pattern X works because of Y. Constraint: don't apply to Z. "
        "Future note: revisit when feature Q lands."
    ),
)

print(result["issue_url"])    # https://github.com/.../issues/42
print(result["comment_url"])  # ...#issuecomment-...

Why a synthesis, not a "done" comment

Closing an issue produces two artifacts:

  • The Issue itself — implementation log. The diff and commit history already show what was done.
  • The closing comment / synthesis — what was learned. Lasts longer than the diff in mental cache.

Good closing comments lead with why, not what. Failure modes, constraints discovered, alternatives rejected. The synthesis is the seed of an institutional memory.

Internal shape

prepare_synthesis ──▶ close_github_issue           [terminal]
                              │
                              └──▶ post_close_callback  [detached, when=callback]

  • validate=must_have_synthesis_text runs against the raw input string. Empty or whitespace-only → FAILED with no GitHub API call. This is structural: callers can't accidentally close-with-no-text.

  • close_github_issue posts the synthesis as a comment, then PATCHes the issue to state=closed, state_reason=completed. Returns the issue URL and comment URL.

  • post_close_callback (optional) runs detached. Caller plugs in any extra work — store synthesis in a memory system, ping a tracker, emit a webhook. Failure here lands in result["detached_failures"] and does NOT bubble up as a close failure. Skipped via when= if the callback isn't provided.

Pluggable post-close callback

python
def store_in_my_memory(synthesis: str, issue_url: str, repo: str, number: int):
    # Whatever your memory layer is — Turso, sqlite, a JSON file, etc.
    db.execute("INSERT INTO learnings (issue, synthesis) VALUES (?, ?)",
               (issue_url, synthesis))
    return {"stored": True}

result = close_issue(
    repo="owner/repo",
    number=42,
    synthesis="...",
    post_close_callback=store_in_my_memory,
)

if result["callback_result"] is None and result["detached_failures"]:
    # The callback failed but the issue is still closed.
    print("Memory store failed:", result["detached_failures"])

The callback receives keyword arguments: synthesis, issue_url, repo, number. Anything it returns goes into result["callback_result"].

Result shape

python
{
    "issue_url":        "https://github.com/owner/repo/issues/N",
    "comment_url":      "https://github.com/.../issues/N#issuecomment-...",
    "comment_id":       12345,
    "callback_result":  <whatever the callback returned, or None>,
    "detached_failures": [],   # populated if callback raised
}

Raises RuntimeError only if the GitHub close itself fails. Callback failures are detached.

Auth

Requires GH_TOKEN (or GITHUB_TOKEN) in the environment. Classic PAT or fine-grained PAT with repo scope (specifically issues:write).

When NOT to use

  • Closing an issue without a synthesis. If you genuinely have nothing to say beyond "done," just gh issue close N directly. This skill is for the synthesis use case.
  • Closing many issues at once (use a script that calls this in a loop — fine, but the flow setup cost per call is small but not zero).

See also

  • flowing — the DAG runner this skill is built on
  • opening-prs — the symmetric "open and merge" flow

© oaustegard, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in closing-issues of oaustegard/claude-skills.

  • SKILL.md
  • CHANGELOG.md
  • scripts/closing_issues.py
  • tests/test_closing_issues.py

Open the folder on GitHubat commit 6fc82b8

Compare with similar skills

Closing Issues next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Closing Issues compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Closing Issues this skilloaustegard/claude-skills150—~1.1kAutomated safety check: PassMIT
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Diagnosing Superpowers Sessionsobra/superpowers296k3 repos~1.7kAutomated safety check: PassMIT
GitHub Deep Researchbytedance/deer-flow83k5 repos~1.3kAutomated safety check: PassMIT
Greplooponyx-dot-app/onyx32k4 repos~3.3kAutomated safety check: PassMIT
Update V8 Versionopeninterpreter/openinterpreter69k2 repos~845Automated safety check: PassApache-2.0

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Works with

Questions about Closing Issues

What does Closing Issues do?

Close a GitHub issue with a synthesis comment as a flowing graph — validate the synthesis, post the closing comment, close, then run a pluggable callback (e.g. Closing Issues is an agent skill from oaustegard/claude-skills.g.

When should I use Closing Issues?

Closing Issues fits situations like: closing an issue should also capture the LEARNING (not just the diff log) and when the post-close work shouldnt block the close ack.

How do I install Closing Issues in Claude Code?

Run `npx skills add oaustegard/claude-skills --skill closing-issues -a claude-code`. Or copy the skill folder (closing-issues in oaustegard/claude-skills) into .claude/skills/closing-issues in your project. Claude Code loads it when a task matches its description.

How do I install Closing Issues in Codex?

Run `npx skills add oaustegard/claude-skills --skill closing-issues -a codex`. Or copy the skill folder (closing-issues in oaustegard/claude-skills) into .agents/skills/closing-issues in your project. Codex loads it when a task matches its description.

Can I use Closing Issues in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add oaustegard/claude-skills --skill closing-issues -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/closing-issues, .gemini/skills/closing-issues, .github/skills/closing-issues and .opencode/skills/closing-issues in your project.

What does Closing Issues need to run?

Going by SKILL.md and its folder, Closing Issues needs Python for the scripts in its folder, the command-line tools its instructions call (gh) and credentials named GH_TOKEN and GITHUB_TOKEN. Our summary lists: Python 3; A credential in GITHUB_TOKEN.

Does Closing Issues access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Closing Issues safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Closing Issues use?

Closing Issues is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Closing Issues use?

About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Closing Issues?

Skills that share tags, products or a category with Closing Issues: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Diagnosing Superpowers Sessions (obra/superpowers, 296k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars) and Greploop (onyx-dot-app/onyx, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Closing Issues?

oaustegard (a GitHub user) maintains it in oaustegard/claude-skills, which has 150 GitHub stars. The repository holds 69 skills in this directory. The repository was last updated on October 8, 2026.

Source: oaustegard/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.