sdlc-radar

# sdlc-radar A proactive research scout — the *supply* side that complements the gap log's *demand* side: it surfaces what you didn't know to look for. **Phase A is dry-run: it writes a digest under `.sdlc/` and records what it surfaced, but never files issues or touches GitHub.** 1. **Agenda (rotate over the backlog).** Get the open backlog — local `.sdlc/goals/*.md`, or `gh issue list --state open` in github mode — and count it (N). Pick this run's slice: `python3 "${CLAUDE_SKILL_DIR}/scripts/radar.py" agenda <N> <k> <cursor>` (k≈3; `cursor` from the last run's `next_cursor`, starting 0). It returns the item indices to research + the next cursor, so successive runs cover different items. 2. **Research (fail-soft).** For each agenda item, research the current SOTA against it — your `WebSearch`/`WebFetch`, or the `deep-research` skill if available (a soft dep). Return cited findings `{topic, summary, url, issue}`. An item that errors is skipped — never abort the run. 3. **Dedup.** Form a short, stable key per finding (e.g. `issue-<n>:<topic-slug>`). Drop any already in the ledger (`radar.py seen .sdlc`) or already a known gap (`kg.py gap list .sdlc`) — don't repeat. 4. **Rank** the survivors by novelty × impact-on-the-item × actionability; tag 🚀 / 🔧 / 📌. 5. **Digest (dry-run write).** Write a ranked markdown digest to `.sdlc/knowledge/radar/<UTC-date>.md` (findings + a short "suggested actions" list), and record each surfaced finding so it isn't ...