| 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","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.
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"])
print(result["comment_url"])
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
def store_in_my_memory(synthesis: str, issue_url: str, repo: str, number: int):
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"]:
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
{
"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": [],
}
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