← ClaudeAtlas

planning-and-researchlisted

Deep web research, competitor scanning, technology evaluation, and implementation planning. Decomposes work into vertical slices, identifies parallel workstreams, tracks assumptions with confidence levels, and designs the critical path for minimum wall-clock time.
heymegabyte/claude-skills · ★ 18 · AI & Automation · score 72
Install: claude install-skill heymegabyte/claude-skills
# 03 — Planning and Research Decompose work into parallel vertical slices using deep web research, competitor scanning, and technology evaluation. ## Deep research protocol Before any non-trivial implementation: 1. Web search top 50 results for primary keyphrase 2. Read top 10 in depth — extract directives + counter-arguments 3. Cross-ref against existing rule mesh 4. Confidence-track every claim 0-1 Use `web_search_20260209` + `web_fetch_20260209` (free when paired with `code_execution_20260120`). ## Competitor scanning For every website build, run `rules/competitor-research.md` Phase -1 BEFORE Phase 0: - Identify top 5-10 audience-comparable sites - Score each on 100-pt rubric (10 dims × 10pts) - Set ≥15% beat-floor for Phase 6 loop termination ## Technology evaluation For every new dep / framework / service consideration: 1. **Already have equivalent?** → use it 2. **Feature truly needed?** → if speculative, defer 3. **License?** → OSS free only (per `rules/brian-preferences.md` priority order) 4. **CF compat?** → adapter pattern per `rules/cloudflare-hostable-supervisor.md` 5. **Bundle/perf impact?** → measure before commit 6. **Lighter existing solution?** → prefer 7. Decide: install now · defer · adapter-only · reject + document why ## Implementation planning ### Decomposition - Identify atomic units (file × layer) - Mark dependencies between units - Distinguish independent vs serial chains ### Vertical slicing Per `06-build-and-slice-loop`: - Each slic