implementation-readiness
implementation-readiness is an Engineering planning & specs skill for AI agents, published by l-gevity in the l-gevity-skills repository on GitHub. Skillspace rates implementation-readiness D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Determines whether graph-structured requirements are ready for architecture, development, and verification, then derives the smallest coherent build-preparation package without inventing requirement meaning. Use when producing capability maps, epics or workstreams, implementation slices, dependency sequencing, contract candidates, domain-model seeds, cross-cutting constraints, acceptance-test references, ADR seeds, technical questions, or explicit ready/partly-ready/not-ready decisions. Do not use for initial discovery or requirement graph normalization.
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 20
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- 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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