research-to-feature
Skill2 starsChanged 3 months agoNo licenceView on GitHub
Produces a single RICE-scored feature recommendation backed by a NotebookLM meta-study and a business use-case review, ready for a developer to pick up and implement. Chains self-discover → notebooklm-meta-study → review-business-use-case → RICE scoring into one pipeline. The trigger phrases are "research a feature for", "evidence-backed feature proposal", "RICE-scored feature from research", "turn research into a feature spec", "meta-study to feature", and "research-to-feature pipeline". Do NOT use for trivial lookups, single-skill tasks, feature ideas without research backing, or any query where the user already has a fully specified feature — this skill generates evidence from scratch.
In this repository6 other files it gives its agents.
- create-skillSkill
- nlm-meta-studySkill
- reasoning-frameworkSkill
- refactor-solo-maintenanceSkill
- review-business-use-caseSkill
- rice-scoringSkill
The file
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We split this skill into the rules it gives an agent
15 rules. About 0 are common, 10 are distinctive, and 5 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈10
Distinctive · estimate
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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