brainstorm

Kit Preamble — brainstorm

Kit Script Root

Kit root: ${CLAUDE_PLUGIN_ROOT}

• Absolute path above → plugin install (substituted at load time; no project scripts/ dir): prefix every kit script command with it, e.g. bash <kit-root>/scripts/checkpoint.sh …. Absolute paths also work from worktrees.
• Literal ${…} placeholder above → standalone layout: run commands as written.

Project Context Detection

Run these checks silently at the start. Use results to adapt behavior:

• [ -f issues.md ] — if true, this project uses the sprint system. Respect issue numbering and STATUS.md.
• [ -f docs/sprint_state.md ] — if true and Status shows running, a sprint is active. Be aware of parallel work in worktrees.
• [ -f docs/prd_digest.md ] — if true, read it for quick project context before starting.

Kit Rules

• Verify gh auth status before any GitHub operation. Steps:

1. Determine the output path ($ARGUMENTS or docs/brainstorm_notes.md).
2. Check if the file already exists at that path.

If the file does NOT exist (New Session):

3a) Ask the user to freely describe their idea, problem, or direction — anything goes. 4a) Discovery phase: Explore the problem space with Socratic questions: - Who has this problem? Why does it matter? - What does success look like? What constraints exist? Ask 1–2 questions at a time. Do not overwhelm. Discovery is conversational and not research-grounded — keep it light. 5a) Existing Landscape research (only this section is research-grounded; per SPEC-018 platform-first delegation): - Probe runtime: python3 scripts/has_skill.py deep-research - Exit 0 OR 2 → primary path: invoke /deep-research with a scoped question about competing solutions / existing tools / market landscape for the user's problem. Pass the report through python3 scripts/synthesize_from_deep_research.py --mode brainstorm to render the Existing Landscape section. Then run the synthesizer-auditor: invoke Task with subagent_type: synthesizer-auditor, inputs = (rendered Existing Landscape draft, /deep-research report). Block save on claim_dropped / claim_distorted / evidence_distorted / scope_change findings. - Exit 1 → degraded path: ask the user for 1–3 source URLs about existing solutions. For each URL: python3 scripts/capture_source.py <url>. Construct each landscape claim per templates/research_claim.md. Validate every claim with python3 scripts/validate_research_claim.py --claim-file <claim>.json; block save on non-ok verdicts. Run Task with subagent_type: research-auditor, inputs = (draft, docs/references/research/). Block save on context_contradicts / scope_change findings. - No source available on either path → render the section as the literal line Data: not available — re-run /deep-research with a sharper question or accept "no data". Never paraphrase to fill in. 6a) Ideation phase: Once the problem is clear, propose 2–3 solution directions with brief pros/cons for each. Help the user narrow down. This step is authored opinion, not research-grounded. 7a) Synthesize findings into the brainstorm notes format (Problem Space, Existing Landscape, Idea Candidates, Decisions).