Apply requirement quality principles when generating or validating feature specifications. Enforces feature completeness, scenario structure, AC verifiability, feature independence, and implementation slice quality. Use when writing feature specs, validating existing requirements, or when the user mentions 'validate this spec', 'check this feature', 'requirement quality', 'is this spec complete', or 'requirement-quality'. This skill governs the craft of writing individual feature specifications — not technical design (see design-blueprint), not implementation (see code-forge).
npx skills add https://github.com/techygarg/lattice --skill requirement-quality
Skill supports project-specific standards. Order:
.lattice/config.yaml in repo rootpaths.requirement_standards for custom doc pathmode:mode: override (or no mode): Custom doc full precedence. Use instead of embedded defaults. Must be comprehensive — sole reference.mode: overlay: Read embedded ./references/defaults.md first, then apply custom doc sections on top. Custom sections replace matching sections in defaults (matched by heading). New sections appended after../references/defaults.mdCustom standards produced by requirement-forge-refiner → consumed by this atom → composed by requirement-forge molecule.
STOP: Before writing any feature file, verify ALL checks. If a check clearly fails → fix before writing. If judgment call (see Ambiguity Signals) → flag and surface options.
If validating an existing spec (not generating), same checks apply — "fix before writing" means "fix before marking approved." Present findings as a quality report with severity.
Draft vs approved enforcement: For status: draft — items 1, 2, 10 are required. Items 3–9, 11, 12 are advisories: flag findings but do not block write. For status: approved — all items required, no exceptions.
10. INDEPENDENCE: Feature is self-contained — no unresolved external unknowns required before design-blueprint can begin? Any unresolved Open Questions affecting scope, behavior, or ACs are blockers unless each is marked non-blocking with a stated reason.
11. IMPLEMENTATION NOTES: Slices ordered chronologically, at the "what" level — no technical implementation specifics?
12. COHERENCE: All scenarios address the same user need in the Problem Statement? If a scenario serves a different need, it belongs in a separate feature.
Project-specific checks: if loaded doc contains a validation checklist section, apply those after base checklist.
When all checks pass: output "Spec passes requirement-quality — ready for write." (pre-write mode) or "Spec passes requirement-quality — status: approved." (validation mode).
STOP: After checklist, scan for these. If found → fix or challenge before writing.
depends_on is empty but feature references another feature's data or behavior in its scenarios → flag missing dependencydepends_on frontmatterFlag these — present options and reasoning. If framework:collaborative-judgment is loaded, use it to structure the presentation.
See ./references/defaults.md for epic/feature/scenario definitions, AC format examples, priority notation, status workflow, naming conventions, and implementation slice guidance.
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementing any feature or bugfix, before writing implementation code
Use when you have a spec or requirements for a multi-step task, before touching code
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Use when writing or improving README files. Not all READMEs are the same — provides templates and guidance matched to your audience and project type.
| Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Official Opentrons Protocol API for OT-2 and Flex robots. Use when writing protocols specifically for Opentrons hardware with full access to Protocol API v2 features. Best for production Opentrons protocols, official API compatibility. For multi-vendor automation or broader equipment control use pylabrobot.
Take techygarg/requirement-quality from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.