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概要と使いどころ
Phase 7 of the SRS workflow. Runs srs_validator.py --dir on the generated SRS files, reports errors and warnings, auto-fixes ERRORs, and outputs a COMPLIANT / PARTIALLY COMPLIANT / NON-COMPLIANT verdict.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill to define and validate the requirements for a Salesforce Partner Relationship Management (PRM) implementation: deal registration flows, lead distribution models, partner tier hierarchies, MDF budget tracking, and co-marketing content entitlement. Trigger keywords: partner community requirements, PRM deal registration setup, channel partner portal requirements, lead distribution partner, partner tier management, MDF tracking, co-marketing entitlement. NOT for implementing the partner sharing model — use data/partner-data-access-patterns. NOT for building the portal in Experience Builder — use admin/experience-cloud-site-setup. More trigger keywords: partner portal design worksheet, partner tier licence and role depth, PartnerAccountId blank on opportunity, portal role Executive Manager User, sharing set does not support Lead, enable partner user greyed out, offboard a partner firm, PartnerMarketingBudget PartnerFundRequest PartnerFundClaim, ChannelProgramLevel partner tier, deal registration acceptance step.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill to gather, document, and validate OmniScript flow design requirements before development begins — covering screen layout requirements, branching logic, data source requirements, and user journey mapping. Trigger keywords: OmniScript requirements, OmniScript BA, OmniScript screen design, OmniScript user journey, OmniScript branching requirements. NOT for building the OmniScript or moving logic into an Integration Procedure — use omnistudio/omniscript-design-patterns. NOT for FlexCard requirements — use admin/flexcard-requirements.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill to elicit, document, and validate CRM Analytics requirements — covering data source mapping (Salesforce object sync vs external connector vs Data Cloud), transformation needs, audience-specific lens or dashboard views, and drill-down path specifications — before any dataset or dashboard is built. Trigger keywords: CRM Analytics requirements, analytics data source mapping, CRM Analytics audience requirements, analytics visualization requirements. NOT for the formula and target behind each KPI — use admin/analytics-kpi-definition. NOT for building the dashboard once requirements are agreed — use admin/analytics-dashboard-design.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill to define, document, and validate KPI metrics for CRM Analytics — covering metric formula design, dimension selection, target-dataset modeling, benchmark setting, and the KPI register that must exist before any dashboard or lens is built. Trigger keywords: KPI definition CRM Analytics, analytics metric design, analytics target attainment, CRM Analytics measures vs dimensions, analytics benchmark. NOT for laying out the dashboard or lens itself — use admin/analytics-dashboard-design. NOT for scoping data sources, audiences, and drill-down paths — use admin/analytics-requirements-gathering.
日本語の概要は準備中です。原文の説明を表示しています。
Create, edit, and validate spell definitions (YAML/JSON) that compose connectors and step commands into end-to-end spells. Use when building new spell definitions, modifying existing ones, or exploring available spell components.
日本語の概要は準備中です。原文の説明を表示しています。
Post-implementation review orchestrator. Launches 5 parallel background sub-agents: Oracle (goal/constraint verification), Oracle (code quality), Oracle (security), unspecified-high (hands-on QA execution), unspecified-high (context mining from GitHub/git/Slack/Notion). All must pass for review to pass. MUST USE after completing any significant implementation work. Triggers: 'review work', 'review my work', 'review changes', 'QA my work', 'verify implementation', 'check my work', 'validate changes', 'post-implementation review'.
日本語の概要は準備中です。原文の説明を表示しています。
MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD. Routes to references/{python,rust,typescript,rust-ub,go}/. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct.
日本語の概要は準備中です。原文の説明を表示しています。
Qualitative quality review of game design documents — answers "is this design good, and does it follow best practices?" — across all three GDD axes: systems, flows, and content types. Fans out adversarial lenses (completeness, clarity, pillar alignment, systems-math, fantasy-delivery, feasibility, scope) plus domain lenses that check it against the game-design rules, each prompted to find problems rather than validate; produces a severity-graded verdict and a two-bucket report (apply-ready fixes vs research), handed to /unikit-gd-apply or /unikit-gd-explore in one move. Scope is inferred: a named system, flow, or content type reviews that document; "all" runs a cross-document review. Use when the user wants a critique, quality judgment, or rules check of the design, e.g. "review the combat GDD", "review the onboarding flow". This is the subjective quality pass — for a mechanical consistency check (numbers, terms, IDs, references matching the registry) use /unikit-gd-verify.
日本語の概要は準備中です。原文の説明を表示しています。
Refine an existing implementation plan with a second iteration. Re-analyzes the codebase for gaps, missing tasks, and wrong dependencies. Use after /unikit-plan or to improve a /unikit-fix plan, or when the user says "improve the plan", "what's wrong with the plan", or "update the plan from research". Optional +check flag validates refinements via a fresh-context subagent.
日本語の概要は準備中です。原文の説明を表示しています。
Record a finding about the configured engine MCP server into .unikit/MCP-RECHECK-NOTES.md — the project's log of what has to be re-checked here. Use right after a call reported success while changing nothing, ate an argument, or validated a broken state, e.g. "write this down", "record this MCP finding", "the server lied — note it", "add a recheck note", "trap this". Takes three forms of input: the finding in one line, a path to a plan file (harvests the "## MCP Findings" table of that plan and nothing else), or nothing at all — then it takes findings already in the session first, and offers to scan the tables of plans touched since the last audit. The table only, never the plan body. Writes in the one allowed genre — a check to perform; never a lifted gate, never a named workaround, never a claim about what the server can or cannot do. Makes zero MCP calls and needs no editor. To replay, retire, or upstream existing notes use /unikit-mcp-audit instead.
日本語の概要は準備中です。原文の説明を表示しています。
Curate the project's knowledge base and memory in .unikit/memory/ — the indexed reference library of coding standards and framework usage patterns. ALWAYS use this skill whenever the user adds knowledge from a source: a URL, a file, a folder path, a PDF, an article, or a book — any path/link/document is a strong signal for the knowledge base, not a quick rule. Also use it to research or document how the project uses a framework, or to add a researched core/stack knowledge entry. Sub-commands by phrasing: "migrate the rules" or "promote rules" runs migrate-rules; "optimize the knowledge base" or "optimize the rules" runs optimise (extract large sections into references); "validate" re-syncs RULES_INDEX.md; "--module <id>" targets a module. For a quick one-line convention or correction typed as a prompt ("always do X", "never use Y", "remember this") with no source, use /unikit-rules; for architecture decisions use ARCHITECTURE.md.
日本語の概要は準備中です。原文の説明を表示しています。
Perform a code review on {{engine_name}} {{engine_code_language}} code. Checks for bugs, security issues, performance problems, and best practices against the project's coding rules, design principles, and framework-specific conventions. Supports four modes — staged changes, a pull request, a commit range, or individual files. Use when the user says "review code", "check my code", "code review", "review PR", "review staged changes", "review these commits", or "is this code okay". Optional +check flag validates findings via a fresh-context subagent.
日本語の概要は準備中です。原文の説明を表示しています。
Customize how a built-in unikit skill behaves in this specific project by writing workflow overrides into its skill-context file. These are per-skill workflow rules (e.g. "/unikit-review should also flag TODO comments", "/unikit-implement should run tests after each task"), not coding conventions. Use when the user wants to change, customize, or override how a particular unikit skill works in this project — "customize the review skill", "make /unikit-fix always add logging here", "the implement skill should do X differently", "add a skill rule for /unikit-commit". Use "validate" to find stale overrides against updated base skills. For a general coding convention (not tied to one skill) use /unikit-rules; to derive rules from past mistakes use /unikit-evolve.
日本語の概要は準備中です。原文の説明を表示しています。
Good-faith divergent brainstorming for achieving a goal. Validates assumptions, then spawns brainstormers running different techniques (first-principles, working-backwards, lateral, analogical, constraints-shift, etc.) in isolation, and synthesizes the pool into a report of standouts, reasonable ideas, and hybrid combinations. Produces feedback only — no code, no tickets, no artifacts.
日本語の概要は準備中です。原文の説明を表示しています。
Proactive bug-hunting workflow. Assesses codebase risk through complexity, coverage, and structural analysis, then spawns focused investigators that write reproducing tests to validate suspected bugs. Thoroughness over speed. Advisory only — produces findings and proposes tickets; does not implement fixes.
日本語の概要は準備中です。原文の説明を表示しています。
Use when estimating one-rep max (1RM), converting between weight and rep ranges, or calculating training loads from a validated percentage-of-max table.
日本語の概要は準備中です。原文の説明を表示しています。
Inspect the effective Spec Kit artifact inventory and composition stacks via `specify artifact`. USE FOR: listing commands/templates/scripts/hooks, explaining which preset or extension layer supplies an artifact, inspecting resolution precedence and hidden layers, checking hook registration, or resolving a stack lookupId to its validated contribution. DO NOT USE FOR: installing or changing presets/extensions (use speckit-preset or speckit-extension), resolving only a preset-managed filename (use speckit-preset), or running an artifact.
日本語の概要は準備中です。原文の説明を表示しています。
Detects tests that validate framework/library behavior (Prisma, Express, bcrypt, JWT, axios, React hooks) instead of OUR code. Returns findings with REMOVE decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Validates decisions via MCP Ref. Reports with SEC-/PERF-/MNT-/ARCH-/BP-/OPT- prefixes.
日本語の概要は準備中です。原文の説明を表示しています。
Builds dependency graph, detects cycles (DFS), validates boundary rules, calculates coupling metrics (Ca/Ce/I, CCD/NCCD). Adaptive architecture detection.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Protocol Buffer (.proto) files, buf.yaml, buf.gen.yaml, or buf.lock. Covers proto design, buf CLI, gRPC/Connect services, protovalidate constraints, schema evolution, and troubleshooting lint/breaking errors.
日本語の概要は準備中です。原文の説明を表示しています。
Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "implement a DiD regression", "run a staggered difference-in-differences", "set up an event study", "implement IV / 2SLS", "run a regression discontinuity design", "build synthetic control", "do propensity score matching", "test parallel trends", "run Honest DiD", "wild cluster bootstrap", "Callaway-Sant'Anna", "Sun-Abraham", "Bacon decomposition", "double machine learning", "debiased machine learning", "DML / DoubleML", "cross-fitting", "causal forest", "heterogeneous treatment effects", "ATE with ML controls", "which causal design fits my data", or needs causal-inference code, diagnostics, or identification writing in Python (StatsPAI), R, or Stata. Based on Scott Cunningham's Causal Inference: The Mixtape, with runnable validated templates, ML-based causal inference patterns, and Journal of Finance applications.
日本語の概要は準備中です。原文の説明を表示しています。