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fatih.bulut 6737558d56 test(market-research): cover v2 scripts in smoke; update README 
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 		2026-06-23 23:13:06 +03:00
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.claude-plugin feat(market-research): scaffold plugin, command, README, marketplace entry 2026-06-22 00:46:09 +03:00
commands feat(market-research): scaffold plugin, command, README, marketplace entry 2026-06-22 00:46:09 +03:00
skills/market-research docs(market-research): fix intro phase count 6->8 in SKILL.md 2026-06-23 23:08:35 +03:00
tests test(market-research): cover v2 scripts in smoke; update README 2026-06-23 23:13:06 +03:00
README.md test(market-research): cover v2 scripts in smoke; update README 2026-06-23 23:13:06 +03:00

README.md

market-research

A Claude Code plugin that autonomously researches the app/game market and surfaces scored, non-repeating clone candidates, then hands user-chosen candidates to the clone-app plugin for feasibility analysis.

What it does

/market-research runs an 8-phase workflow (0–7):

  1. Seed rotation — pick varied search angles (category × region × niche) so runs differ.
  2. Gather — App Store RSS (fetch-charts.py) + play.google.com charts (fetch-play-charts.py) + Google Trends best-effort (trends.py) + free web search.
  3. Synthesize — cluster findings into ≥10 distinct app/game ideas.
  4. Score — composite numeric score: cloneability 35 + market 35 + monetization 20 + niche 10 (see scoring-guide.md + numeric-sources.md).
  5. Dedup — exclude anything already in ./work/market-research/history.json.
  6. Present — show the scored, ranked table.
  7. Survivor-only enrichment — for user-chosen candidates only: resolve the Play Store package ID (play.py) and verify the link is live via WebFetch before handing off.
  8. Handoff — chosen candidates (with verified Play links) flow into clone-app.

State

Written under ./work/market-research/ in your current directory:

  • history.json — every past suggestion; the non-repeat memory.
  • research-<date>.md — the full report for a run.

Scripts

  • scripts/fetch-charts.py — fetch Apple App Store RSS chart feeds → normalized JSON.
  • scripts/fetch-play-charts.py — fetch play.google.com top/category charts → normalized JSON (no AppBrain; uses the public Play web endpoint directly).
  • scripts/play.py — resolve an app name or bundle ID to a Play Store package ID and count search results (used in survivor-only enrichment, Phase 6).
  • scripts/trends.py — best-effort Google Trends interest data for a keyword; never hard-fails (falls back to null if the endpoint is unavailable).
  • scripts/history.py — read / append / dedup the suggestion history.

Python is stdlib-only. Tests run offline against tests/fixtures/:

bash plugins/market-research/tests/run-all.sh

References

AI-judgment rubrics under skills/market-research/references/:

  • research-angles.md — rotating category × region × niche seeds for run-to-run variety.
  • scoring-guide.md — the 0–100 weighted composite formula and per-dimension guidance.
  • numeric-sources.md — how to map raw data (chart rank, install count, rating, search results) to numeric sub-scores used by scoring-guide.md.
  • report-template.md — output format for the scored candidate table and per-candidate write-ups.

Effort convention

Effort is measured in AI Sprints (one focused Claude session), never calendar time.