Accelerated-Innovation

Plan implementation work as a sequence of the smallest independently demonstrable increments. Use when given a feature request, a body of work, or any implementation task that must be broken down or sequenced BEFORE coding — it classifies the request, identifies the next demonstrable behaviors, and recommends (advisory) an appropriate model tier for implementing each increment. This skill plans; it does not write code, tests, commits, or architecture.

Write or improve unit tests following a strict determinism, F.I.R.S.T., and fast-feedback-budget discipline. Use when asked to write tests, improve tests, review test quality, classify tests, or assess a test suite against a 30-second fast-feedback budget. Invokes a structured output protocol that identifies behaviors under protection, classifies each test by level and feedback loop, and flags nondeterminism risks.

Standards for writing, reviewing, and evaluating unit tests. Use whenever writing new tests, reviewing existing tests, deciding what to test, assigning a test to a fast vs. full feedback loop, or diagnosing flaky, slow, or low-value tests. Covers structural fidelity, the FIRST properties, behavioral invariants, and coverage-as-diagnostic.

Zero-One-Many Representation Evolution — use this skill whenever working with existing code that needs to change, grow, or be refactored. Triggers include: "refactor this", "add a new X to this", "this is getting messy", "how should I represent this", "there's a lot of duplication here", or any time numbered variables, growing conditionals, repeated parameter groups, or scattered constants are observed. Also use proactively when reviewing code for design quality, assessing coherence and development level, or applying the 8 Code Virtues framework. Do not wait to be asked — if you see representation pressure in the code, surface it.

Author an Architecture Decision Record for a new pattern, exception, or boundary change. Use when the user asks to write an ADR or invokes /govkit-adr-author.

Validate architecture boundaries, standards alignment, and ADR need before planning a feature. Use when starting a new feature or invoking /govkit-architecture-preflight.

Generate an ordered implementation checklist with evaluation compliance summary from a validated preflight. Use when the user asks to draft implementation steps or invokes /govkit-implementation-plan.

Generate a feature plan (plan.md) and eval_criteria.yaml from NFRs and acceptance scenarios. Use when the user asks to plan a feature or invokes /govkit-spec-planning.

Review generated feature specs (Gherkin, NFRs, evaluation criteria) before GovKit execution. Use for refinement conversations where Product, QA, and Engineering improve a draft together before AI-assisted coding starts. Tool-agnostic; works with any generator (e.g. Aha!) and any tracker (e.g. Azure DevOps, Jira). Trigger whenever the user mentions Gherkin, acceptance criteria, feature refinement, 3 Amigos, Draft 0, Development Token, spec review, PM pre-review, QA evidence review, or asks to review, score, or rewrite a feature spec before coding begins — even if they don't name GovKit explicitly.

Generate synthetic test data for a GovKit feature package using Python Faker — a seeded, repeatable generator script plus committed data files derived from the feature's Gherkin scenarios. Use whenever the user asks to "generate test data", "create synthetic data", "seed data", "fixtures", "fake data", "sample records", or "load-test data" for a feature, work item, or acceptance.feature — even if they don't say GovKit or Faker. Also use after a feature package passes readiness and the team needs data to exercise the scenarios. Works for any target stack; only the generator itself is Python.

Emit structured Tier 1 metric events (NDJSON) from a GovKit-governed repository's exhaust — feature packages, .govkit/marker.json, eval_criteria.yaml, CI gate runs, PR exports, and git history. Use this skill whenever the user wants to compute, emit, export, or audit delivery/quality metrics from a GovKit repo: spec completeness scores, gate-readiness audits, metric event streams for an aggregator, velocity/quality pair inputs, or "which features aren't gate-ready." Trigger on mentions of GovKit metrics, metric events, telemetry emission, feature package audit, spec completeness, or AIPOS Tier 1 metrics — even if the user doesn't name this skill.

One clear sentence on what this skill does AND when Claude should use it. Include the trigger words a user would actually type (e.g. "readiness score", "spec review"), because this description is the only thing Claude sees when deciding whether to load the skill.

Author an Architecture Decision Record for a new pattern, exception, or boundary change

Run before planning any feature to validate architecture boundaries, standards alignment, and ADR need

Generate an ordered implementation checklist with evaluation compliance summary from a validated preflight

Generate a feature plan (plan.md) and eval_criteria.yaml from NFRs and acceptance scenarios