discovery-research-stinger
discovery-research-stinger is a User interviews & surveys skill for AI agents, published by legioncodeinc in the that-git-life repository on GitHub. Skillspace rates discovery-research-stinger B (80/100) and it passed the safety scan; the rating is based on static analysis only.
Continuous product discovery coach — Teresa Torres interview cadence, Opportunity Solution Trees, Jobs-to-be-Done interviews, prototype testing, and the "build less, learn more" loop. Use when the user says "run a discovery session", "build an OST", "write an interview script", "map our assumptions", "design a prototype experiment", "weekly discovery summary", or when a team is unsure what to build next and needs to run discovery before planning. Do NOT use for shipped-feature usability testing (quality-worker-bee), UI design decisions (ux-ui-worker-bee), PRD authorship (library-worker-bee), or analytics result interpretation.
- Grade
- B
- Quality
- 80 / 100
- Safety
- Passed
- GitHub stars
- 72
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.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 99 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 1 other repositories, in 0 collections
- Scope
- Portable: works in any project. General continuous discovery, OST and JTBD interview methodology
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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