/issue-match — knock here, or walk past?

🧒 End the report to a non-technical owner with an "In plain words" block ([[eli5-always]]).

The owner's rule from 2026-07-25 ([[cold-pr-into-silent-queue]]): a cold PR into a silent queue is not a contribution, it's noise. Measuring the queue is the first step, BEFORE writing any code. This skill turns that measurement into a button instead of hand-driving gh in every session.

Measured 07-25 on anthropics/claude-cookbooks: 220 open PRs, median age 47 days, 51% without a single comment, 67% of merges happened within a day of submission (which means the agreement existed BEFORE the PR). We had 6 open there, 5 cold, 0 merged. The only one a human reacted to was the one that came in through someone else's open issue.

How to run it

python "$USERPROFILE/.claude/scripts/issue_match.py" anthropics/claude-cookbooks --artifact "search agent, adversarial verify"

Command	What it does
<owner/repo>	measure a single repo
--artifact "kw1, kw2"	the main parameter — the keywords of our artifact, used to find the door
--all	fan out across every repo in the config (~5s per repo; 14 repos ≈ 70s)
--init	build the config from OUR PR history (gh finds where we submitted)
--live-days N	an issue counts as live if it was updated within N days (default 30)
--json	machine-readable output
--no-draft	skip the entry draft

Config: ~/.claude/issue_match.json. Exit codes: 0 measurement done · 2 bad arguments · 4 gh unavailable or all fetches failed.

How to read the output

1. QUEUE — open PRs (the exact count, not truncated by a limit), median age (when sampled, this is a lower bound, the real one is higher), the share with no comments, the merge pattern. If "merged on the day of submission" is ≥60%, that is not "they merge fast", that is pre-agreement; a cold PR will not reproduce that rhythm. Look at one-time authors: if none of the merges came from a one-time author, the repo merges only its own people, and a healthy median promises an outsider nothing.
2. US THERE — how many of our PRs are sitting and how many got no reaction. Many cold ones = warm those up first instead of spawning new ones.
3. DOORS — live third-party issues matching the keywords. Our own issues are counted separately: your own door is not an invitation.
4. VERDICT — 🟢 enter through an issue · 🟡 open our own issue and wait · 🔴 don't push · ⚪ not measured (the issue fetch failed, or the door may have fallen outside the sample) — do not make a decision on that data, run the measurement again. A silent fetch is not an answer.

⚠️ Without --artifact a 🟢 verdict is deliberately withheld: the match was never checked, and a fresh issue on its own is not yet our door. Broad words ("agent", "memory") produce 🟢 almost everywhere — that is honest noise, not a find; narrow them to the essence of the artifact and read the ← matched: line.

Boundaries

• READ-ONLY. The skill sends nothing. A comment in someone else's thread and a PR are outbound → a human sends them (or I do under the mandate [[ship-github-no-plus-wait]], but signed and after the quality gate).
• Matching works on words in the title, labels and issue body. That is a crude filter, not comprehension; the final "is this our thread or not" is a human call over the list.
• With >100 open PRs the median age is computed over the newest ones → it is understated. That is flagged in the report.
• Issue liveness = human activity (the last comment by a LIVE human, or the issue being opened by a human), not updatedAt: that field is bumped by labels and bots, and a "bump" from Dependabot/stale would look like a live door. Bot comments are counted separately and never count as liveness.
• Where it matched matters. A match in the title or a label = on-topic; one generic word in the body (auth, fix, token) = more likely a collision, and no 🟢 is granted for it (you need either a title/label hit or ≥2 words in the body). The ← matched line shows exactly where.
• The merge median is global per repo: it mixes all PR types (a typo fix and a new recipe) and does not show the queue for a specific area. A guide, not a verdict — if our artifact is narrow, look by hand at how PRs in exactly that area moved. (Raised by the external reviewer Codex, 07-27; fixing it with a path filter = added complexity, not taken for now.)
• Check the commit/PR signature BEFORE sending ([[signature-is-part-of-the-work]]) — 16 of 20 PRs went out signed by an empty account.

Further down the pipeline

🟢 → a comment in the thread → the maintainer answers → a PR referencing the issue → pr_watch.py watches for a reaction → a scheduled bump. 🔴 → don't push into this repo; the cold PRs already sitting there get warmed up (tie each one to the issue it answers) instead of adding a ninth.

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Like this skill? It is one of 100 in second-brain-starter-kit: the second brain we built for ourselves and run every day at Palo Alto AI Research Lab. Install the whole set with npx skills add tonydzi/second-brain-starter-kit. Everything is open source and free, so take what you need.

Flagships worth a look on their own: secondop-panel (a second opinion from a panel of external models), claude-memory-tidy (stop your agent's memory from rotting), telegram-mcp-kit (your own Telegram over MCP in about 15 minutes).

Author: Anton Dziatkovskii, Palo Alto AI Research Lab. Telegram @tonydzi - WhatsApp +1 341 222 9178 - X @Tony_Stef_

Engineers: want to test-drive this setup? Message me. I hand out free starter seeds to engineers who test and report back, and custom skill requests are welcome.