product-discovery

product-discovery is a Multi-stage workflow orchestration skill for AI agents, published by theagenticguy in the erpaval repository on GitHub. Skillspace rates product-discovery D (66/100) and it passed the safety scan; the rating is based on static analysis only.

File-first orchestrator for product discovery and spec frameworks. Frames the problem with a Discovery Lead / Product Analyst / System Architect role, spawns parallel framework agents (Double Diamond, How Might We, Jobs to Be Done, user stories + INVEST, EARS for AI-coder specs, Gherkin), synthesizes into a PRD or discovery memo, runs a critic pass. Absorbs prd-drafter (idea to PRD via 3 parallel research roles) and design-thinking (pain-point excavation, landscape research, brainstorm). Ships per-framework references, role prompts, templates for PRDs, HMW outputs, job stories, EARS specs. Use when the user asks to write a PRD, draft requirements, run discovery, brainstorm a product, turn insights into HMW questions, write job stories, spec a feature in EARS for Kiro or Spec Kit, define user stories with INVEST, run a Double Diamond round, or mentions JTBD, acceptance criteria, Kiro spec format. Do NOT use for business strategy (Rumelt, Wardley, PR-FAQ as leadership artifact) — use…

Grade
D
Quality
66 / 100
Safety
Passed
GitHub stars
25

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

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Our review

Architecture
84 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

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  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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