--- name: gh-quick-wins description: > Surface low-blast-radius backlog items in the current GitHub repo, ranked by impact. Trigger this skill whenever the user types /gh-quick-wins, says "show me quick wins", "what can I knock out", "low effort items", "low blast radius backlog", "what's the easiest thing to ship", "what's small enough to do quickly", "what's the most actionable issue right now", or any similar request for a filtered, ranked view of the backlog that emphasises bounded-risk, high-impact work. Hybrid: deterministic script exclusion pass + LLM ranking by impact / blast-radius. --- # /gh-quick-wins Two-step recipe. The script applies a deterministic exclusion filter to the open-issue backlog — paginated in full, up to a bounded `--limit` cap — and emits the surviving candidates as JSON. The LLM ranking pass then reads those signals and produces a top-10 markdown table ordered by `impact / blast_radius`. Step 1 is zero-LLM; step 2 is the only place LLM tokens are spent. **Blast radius** is the load-bearing concept — not effort. A one-line `CLAUDE.md` typo fix is low effort but high blast radius (every future session is affected). A full Excalidraw reference guide is high effort but low blast radius (new file, isolated). This skill ranks by blast radius first, impact second. ## Step 1 — Run the deterministic script Run the script and capture its stdout. The interpreter path differs between Windows (Git Bash: `Scripts/python.exe`) and POSIX (`bin/python`); pick the one that exists: ```bash PY="${CLAUDE_PLUGIN_DATA}/venv/Scripts/python.exe" [ -f "$PY" ] || PY="${CLAUDE_PLUGIN_DATA}/venv/bin/python" "$PY" "${CLAUDE_PLUGIN_ROOT}/scripts/gh-quick-wins.py" ``` The script exits 0 and prints a JSON array. Each surviving issue object includes a `signals` sub-object with: - `touches_load_bearing` (bool) — body or title references `CLAUDE.md`, `agents/`, `skills/`, `hooks/`, or `deploy.py`. - `body_appears_drafted` (bool) — body is long (>800 chars) AND contains a fenced code block, markdown table, or >3 `###` headers. True means the issue body already contains the deliverable text. - `comment_count` (int) — length of the comments array. - `days_since_update` (int) — days since `updatedAt`. - `label_set` (list[str]) — label names on the issue. If the script exits non-zero, surface its stderr and stop. The script supports `--repo owner/repo`, `--max-ac N`, and `--limit N` flags. Pass them through if the user specifies a different repo or checkbox threshold. The fetch paginates through the full open-issue backlog up to `--limit` (default 5000); if the backlog exceeds the cap the script prints a truncation warning to stderr and processes only the first `--limit` issues — the view is bounded but never silently truncated. ## Step 2 — LLM ranking pass Read the JSON from Step 1. Rank the surviving issues using the rubric below. Render a top-10 markdown table; if zero issues survived, render the zero- survivor message. ### Scoring rubric **Blast radius** (lower is better for quick-wins): - `low`: New file under `docs/`, `.tmp/`, or a single isolated doc file. `touches_load_bearing` is False and the change scope is self-contained. - `med`: `touches_load_bearing` is True — references `CLAUDE.md`, `agents/`, `skills/`, `hooks/`, or `deploy.py`. These affect every future session; downweight them even if they look small. There is no `high` blast-radius tier in this output — items with clearly unbound blast should have been excluded by label (`epic`, `umbrella`) or prose (`blocked by #N`). If a load-bearing item slips through, label it `med` and let impact be the tiebreaker. **Impact** (higher is better): - `high`: `body_appears_drafted` is True (issue body already contains the deliverable — a new file's full content, a design already written out); OR `comment_count >= 3` (active external interest); OR `documentation` label on a user-facing surface (README, getting-started guide, public reference doc). - `med`: Isolated bug fix, small scoped feature, minor UX improvement. - `low`: Internal-only cleanup, single-line typo, no user-facing effect. **Rank** by: `blast=low` before `blast=med`; within same blast tier, rank `impact=high` before `impact=med` before `impact=low`; within same blast+ impact, rank by `days_since_update` ascending (fresher first). ### Output format Render as a markdown table with these columns: | `#` | `Title` | `Labels` | `Blast` | `Impact` | `Why` | - `#` — issue number as a link: `[#N](url)`. - `Title` — issue title, truncated to ~60 chars if needed. - `Labels` — `label_set` joined by `, `. Empty if none. - `Blast` — `low` or `med` per rubric above. - `Impact` — `low`, `med`, or `high` per rubric above. - `Why` — one sentence, max ~12 words, explaining why this is a quick win. Cap the table at **10 rows**. If more than 10 survived the filter, add a footer line: > _Showing top 10 of N filtered candidates._ If zero issues survived the filter, render: > _No low-blast-radius candidates in the current backlog._ Do not paraphrase or re-render the script's JSON — use its `signals` fields as the scoring inputs and produce the table directly. ## Notes - Step 1's JSON is the structural source of truth for issue data. Do not fetch issues a second time or call `gh issue list` again in step 2. - The `touches_load_bearing` signal is a strong downweight, not a hard exclude. An issue touching `CLAUDE.md` can still appear as `blast=med` if its impact is high — it just ranks below equivalent `blast=low` items. - `body_appears_drafted=True` is the strongest positive impact signal because it means the deliverable is already written. Shipping it is mostly a copy-paste from the issue to a new file. - This skill is read-only. It does not create, label, assign, or close issues. The user always acts on the output themselves. ## Validation Two reference issues calibrate the scoring. Use these to verify the rubric stays calibrated after any changes to the skill body: **#789 — Excalidraw MCP server reference guide (PARAGON: HIGH quick-win)** - `touches_load_bearing`: False (new standalone file, no harness paths in body or title). - `body_appears_drafted`: True (body contained the full reference guide text — a fenced code block, multiple headers, table of contents). - Labels: `documentation`. - Expected scoring: `Blast=low`, `Impact=high`. This is the archetype the skill is optimised for — content already exists in the issue, blast is zero, the `documentation` label confirms user-facing value. **#800 — bash-as-default migration (PARAGON: LOW / filtered)** - This issue would have been excluded at the deterministic filter stage by either the `umbrella` or `epic` label (it was a multi-step migration touching many harness files). - If it somehow survived filtering (e.g. in a repo without those labels): `touches_load_bearing`: True (CLAUDE.md, agents/, hooks/ all in scope). `body_appears_drafted`: True (detailed implementation plan in body). Expected scoring: `Blast=med`, `Impact=high`. Ranks below any equivalent `Blast=low` item despite high impact — the harness-wide blast radius overrides the drafted-body signal. If #789 does not score `Blast=low, Impact=high` in your output, the rubric has drifted. Re-check `touches_load_bearing` and `body_appears_drafted` against the signals the script emitted.