
Optimizes a measured latency, throughput, memory, CPU, or I/O problem through profiling and keep-or-discard experiments. Use for a known bottleneck; not unbiased A/B comparison.
Prepares and publishes a tagged GitHub release from repository evidence. Use for an explicit release request; not for ordinary commits, packages, or community news.
Audits cross-cutting code health across security, delivery, maintainability, dependencies, diagnosability, concurrency, and lifecycle. Use when no specialist audit is primary.
Audits implemented architecture fitness, boundaries, contracts, dependency topology, structure, and configuration ownership. Use for system structure; not implementation-plan review.
Creates and runs reproducible acceptance tests for stated requirements using project-native tooling. Use when executable acceptance evidence is needed; not for audits or product fixes.
Designs a risk-based test strategy and prioritized scenarios without changing code. Use when requirements need a test plan; not for auditing or implementing tests.
Reviews a completed scoped change and its affected runtime and contract paths. Use to find change-caused defects and verify readiness; not for codebase audit, implementation, or repair.
Reviews implementation plans against repository evidence and current authoritative guidance. Use before execution to expose gaps and risks; not for completed delivery review.
Compares tools or implementations through reproducible A/B workloads, correctness oracles, and controlled measurements. Use to choose alternatives; not to optimize a known bottleneck.
Modernizes a bounded capability by removing obsolete custom mechanisms or reducing bundle and maintenance cost. Use for proven modernization value; not routine upgrades or tuning.
Audits whether an existing test suite proves important product behavior with strong, isolated tests. Use when test confidence is uncertain; not to design or implement new tests.
Drafts and publishes fact-checked GitHub Discussions announcements. Use for releases, updates, or project news; not for release creation or issue responses.
Reviews standalone skills and their configured distribution surfaces before publication. Use for skill release readiness; not for product code or implementation-plan review.
Validates, commits, pushes, and remotely verifies approved repository changes. Use when publication is requested; not for releases, package publishing, or announcements.
Audits queries, transactions, data-path performance, and persistence resource lifecycle. Use when data correctness or scalability is at risk; not for general performance tuning.
Audits documentation and code comments for structure, coverage, factual accuracy, and maintainability. Use for documentation trust reviews; not code, test, or architecture audits.
Evaluates new product directions using current demand, acquisition, competition, economics, and validation evidence. Use before commitment; not for backlog or implementation planning.
Upgrades dependencies across package managers with breaking-change research and rollback-safe verification. Use for dependency maintenance; not general code modernization.
Checks evidence-backed duplication, over-abstraction, and unused extensibility. Use when auditing DRY/KISS/YAGNI risk.
Checks dependency health and generic custom utility/integration replacement opportunities. Use when auditing dependency and reuse risk.
Checks local maintainability hotspots: complexity, long methods, god modules, signatures, algorithms, and constants. Also flags identifier drift across API/DTO/DB layers. Use when auditing code hotspots.
Replans Stories by comparing IDEAL vs existing (KEEP/UPDATE/OBSOLETE/CREATE). Use when Epic requirements changed and Stories need realignment.
Checks build, lint, type, test, and CI delivery gate failures. Use when auditing whether the project can reliably ship.
Checks document semantic content against SCOPE and project goals, coverage gaps, off-topic content, SSOT. Use when auditing documentation relevance.
Audits architecture config boundaries: typed settings, scattered env reads, config leakage, and layer ownership. Use for config architecture.
Creates reference docs (ADRs, guides, manuals) for nontrivial tech stack choices. Use when project needs justified architecture decision records.
Checks diagnosability through structured logs, metrics, traces, correlation IDs, and useful log levels. Use when auditing incident visibility.
Checks application security boundaries: secrets, injection, XSS, input validation, and sensitive env defaults. Use when auditing exploitable code paths.
Finds code that can be safely deleted: unreachable, unused, obsolete compatibility, and commented-out code. Use when pruning dead code.
Creates task management docs (kanban board, workflow rules) with configured tracker integration. Use when setting up task tracking for a project.
Checks runtime lifecycle and config validation: bootstrap, shutdown, probes, cleanup, env sync, and fail-fast startup. Use for runtime readiness.
Checks redundant fetches, N+1 loops, over-fetching, missing bulk operations, wrong caching scope. Use when auditing query efficiency.
Checks layer, resource ownership, and orchestration boundaries. Use when auditing architecture boundary enforcement.
Finds architecture-level modernization opportunities: obsolete custom mechanisms, overbuilt extension points, and simplifiable architecture. Use when auditing architecture evolution.
Identifies missing tests for unique critical local logic: money, auth, permissions, data integrity, algorithms, and domain rules. Use when auditing critical logic coverage gaps.
Audits whether one implemented architectural pattern fits project needs and best practices. Use when checking pattern fitness.
Creates slash commands from procedural doc sections. Use when transforming documentation prose into executable commands.
Creates infrastructure.md and runbook.md (Docker-conditional). Use for DevOps documentation in any project.
Reviews skills (D1-D11 + M1-M6 criteria) or .claude/commands for quality. Use when validating skill correctness before release.
Creates design_guidelines.md with WCAG 2.1 compliance and design system docs. Use when project has a frontend.
Creates test documentation (testing-strategy.md, tests/README.md) with Risk-Based Testing philosophy. Use when setting up test strategy for a project.
Extracts procedural content from project docs into slash commands. Use when docs contain deploy, test, or troubleshoot procedures.
Responds to unanswered GitHub discussions and issues with codebase-informed replies. Use when clearing community question backlog.
Creates backend docs (api_spec.md, database_schema.md). Use when project has backend API or database.
Builds dependency topology, detects cycles, validates import rules, and calculates coupling metrics. Use when auditing architecture topology.
Creates root documentation files (AGENTS.md, CLAUDE.md, docs/README.md, standards, principles). Use for initial project doc setup.
Coordinates project documentation creation with single context gathering and project type detection. Use when generating project docs subset.
Creates core project docs (requirements, architecture, tech stack, patterns catalog). Use for any project regardless of type.
Checks transaction scope, missing rollback handling, long-held transactions, trigger/notify interaction. Use when auditing transaction correctness.
Checks races, deadlocks, async hazards, TOCTOU, blocking I/O, and shared resource contention. Use when auditing concurrency correctness.
Checks session scope mismatch, missing cleanup, pool config, error path leaks, resource holding. Use when auditing resource lifecycle.
Checks blocking IO in async, unnecessary allocations, sync sleep, string concat in loops, redundant copies. Use when auditing runtime performance.
Checks layer leakage in method signatures, missing DTOs, entity leakage to API, inconsistent error contracts. Use when auditing API contracts.
Audits physical architecture structure: modules, domains, layer layout, junk drawers, and framework placement. Use for structure drift.
Composes and publishes announcements to GitHub Discussions. Use when sharing releases, updates, or news with the community.
Launches RFC and debate discussions on GitHub. Use when proposing changes that need community input or voting.
Creates complete project documentation system (project docs, reference, tasks, tests). Use when bootstrapping docs from scratch or regenerating all.
Verifies claims in .md files (paths, versions, counts, configs, endpoints) against codebase, cross-checks contradictions. Use when auditing docs accuracy.
Checks hierarchy, links, SSOT, compression, requirements compliance, freshness, legacy cleanup. Use when auditing documentation structure.
Analyzes community health and delegates engagement tasks. Use when managing GitHub issues, discussions, and announcements.
Produces prioritized triage report from open GitHub issues, PRs, and discussions. Use when reviewing community backlog.
Use when auditing persistence and runtime performance through the evaluation platform with mandatory research, coordinated data-layer workers, and structured summaries.
Audits manual test evidence quality: reproducibility, fail-fast behavior, expected evidence/golden files, idempotency, and documentation. Use when auditing manual tests.
Audits assertion strength and test oracles that prove real defects. Use when finding weak tests that execute code but prove little.
Audits whether test results can be trusted: flakiness, isolation, real external dependencies, time/random/order dependency, and shared state. Use when auditing test trustworthiness.
Use when auditing architectural patterns through the evaluation platform with mandatory best-practice research, coordinated pattern workers, and structured summaries.
Audits E2E coverage for critical user-visible journeys and wasteful E2E tests. Use when reviewing E2E journey value.
Audits test maintainability and structure: layout drift, orphan tests, fragmented duplicates, test-to-source mapping, and domain grouping. Use when auditing test suite organization.
Detects tests proving platform behavior instead of local product behavior. Use when auditing product-behavior focus.
Scores each test by portfolio value and returns KEEP/DELETE/MERGE/REWRITE. Use when pruning test-suite cost.
Use when auditing the test surface through the evaluation platform with mandatory research, coordinated test audit workers, and structured summaries.
Performs manual testing of Story AC via executable bash scripts in tests/manual/. Use when Story implementation needs hands-on AC verification.
Plans automated tests (E2E/Integration/Unit) using Risk-Based Testing after manual testing. Use when Story needs a test task with prioritized scenarios.
Use when auditing the codebase through the evaluation platform with mandatory research, coordinated domain audit workers, and structured summaries.
Checks inline code documentation quality: WHY-not-WHAT, density, forbidden content, docstrings quality, actuality, legacy cleanup. Use when auditing comments and docstrings.
Use when auditing project documentation through the evaluation platform with mandatory research, coordinated audit workers, and structured summaries.
Checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Use when implementation tasks are Done and need quality scoring.
Runs existing test suite to catch regressions after implementation changes. Use when Story needs regression verification. No status changes.
Auto-fixes low-risk tech debt (unused imports, dead code, commented-out code) with >=90% confidence. Use when audit findings need safe automated cleanup.
Orchestrates test planning pipeline: research, manual testing, automated test planning. Use when Story needs comprehensive test coverage planning.
Analyzes application logs: classifies errors, checks log quality, maps stack traces to source. Use when logs need review after test runs or during development.
Story-level quality gate with 4-level verdict (PASS/CONCERNS/FAIL/WAIVED) and Quality Score. Use when Story is ready for quality assessment.
Use when coordinating story quality evaluation with mandatory research, worker summaries, agent review, regression evidence, and bounded refinement.
Researches real-world problems, competitor solutions, and customer complaints for a feature domain. Use before test planning to ground tests in actual user pain points.
Reviews task implementation for quality, code standards, and test coverage. Use when task is in To Review. Sets task Done or To Rework.
Fixes tasks in To Rework by applying reviewer feedback, then returns to To Review. Use when task was rejected during review.
Executes implementation tasks through Todo, In Progress, To Review. Use when task needs coding with KISS/YAGNI. Not for test tasks.
Executes test tasks (label 'tests') through Todo to To Review with risk-based limits. Use for test task execution. Not for implementation tasks.
Creates implementation, refactoring, and test tasks from templates. Use when an approved task plan needs tasks created via the configured tracker provider and reflected in kanban.
Use when an evaluation run needs mandatory official-doc, MCP Ref, Context7, and current best-practice research with a structured research summary.
Compares ideal plan vs existing tasks and applies KEEP/UPDATE/OBSOLETE/CREATE changes. Use when Story tasks need re-sync with updated requirements.
Creates or replans 3-7 Epics from scope using Decompose-First pattern. Use when initiative needs Epic-level breakdown or Epic scope changed.
Use when an evaluation run needs review-driven documentation updates and a structured documentation summary.
Use when an evaluation coordinator needs normalized findings from target artifacts and research evidence.
Executes Story tasks in priority order (To Review, To Rework, Todo). Use when Story has planned tasks ready for implementation.
Use when an evaluation run must merge research, findings, documentation, and repair outputs into one verified result.
Use when an evaluation run requires bounded iterative refinement with trace and cleanup evidence.
Use when accepted findings require bounded repair changes and a structured repair summary.
Analyzes Story and builds optimal task plan (1-8 tasks), then routes to create or replan. Use when Story needs task breakdown or replanning.
Use when validating Stories, plans, or tasks through the evaluation platform with mandatory research, parallel evidence lanes, sequential merge, and bounded refinement. Modes: story | plan_review.
Creates Story documents with 9-section structure and INVEST validation via the configured tracker provider. Use when Epic has an IDEAL plan ready for Story generation.
Decomposes scope into Epics, Stories, and RICE priorities. Use when user has project scope and wants full Agile breakdown.
Discovers growth opportunities using Traffic-First KILL funnel. Use when searching for next product direction with validated demand.
Creates, replans, or appends 5-10 Stories per Epic with standards research and multi-epic routing. Use when Epic needs Story decomposition.
RICE-scores Stories with market research and generates prioritization table. Use when Stories need business priority ranking for sprint planning.
Drives a Story through full pipeline (tasks, validation, execution, quality). Use when executing a Story end-to-end from kanban board.
Use when inspecting health, drift, logs, auth, ports, systemd, tmux, or safe repair needs for one VPS project environment.
Use when bootstrapping or managing VPS agent environments: fresh install, add project, hex-relay redeploy, diagnostics, or fleet plan/apply.
Use when deploying, redeploying, verifying, migrating, or syncing users for the hex-relay Telegram/API control plane on a VPS.
Use when creating or verifying one project runtime on a prepared VPS, including god-session, provider credentials, and local dispatcher setup.
Use when installing, verifying, or updating the shared VPS host runtime for Claude Code, Codex, MCP, and marketplace plugins.
Use when accepted findings require bounded repair changes and a structured repair summary.
Use when validating optimization plans through the evaluation platform with mandatory research, parallel agent evidence, sequential merge, and bounded refinement.
Reviews skills (D1-D11 + M1-M6 criteria) or .claude/commands for quality. Use when validating skill correctness before release.
Use when validating Stories, plans, or tasks through the evaluation platform with mandatory research, parallel evidence lanes, sequential merge, and bounded refinement. Modes: story | plan_review.
Use when an evaluation run needs review-driven documentation updates and a structured documentation summary.
Use when coordinating story quality evaluation with mandatory research, worker summaries, agent review, regression evidence, and bounded refinement.
Use when an evaluation coordinator needs normalized findings from target artifacts and research evidence.
Drives a Story through full pipeline (tasks, validation, execution, quality). Use when executing a Story end-to-end from kanban board.
Executes Story tasks in priority order (To Review, To Rework, Todo). Use when Story has planned tasks ready for implementation.
Creates slash commands from procedural doc sections. Use when transforming documentation prose into executable commands.
Story-level quality gate with 4-level verdict (PASS/CONCERNS/FAIL/WAIVED) and Quality Score. Use when Story is ready for quality assessment.
Creates complete project documentation system (project docs, reference, tasks, tests). Use when bootstrapping docs from scratch or regenerating all.
Builds and queries code knowledge graph for dependency analysis, references, implementations, and architecture overview. Use when starting work on unfamiliar codebase or before refactoring.
Upgrades npm/yarn/pnpm dependencies with breaking change handling. Use when updating JavaScript/TypeScript dependencies.
Use when removing Claude-side hex-line integration surfaces such as MCP registration, permissions, hooks, and output style.
Builds and launches Docker containers with health verification. Use when validating that containerized services start correctly.
Creates AGENTS.md canonical and CLAUDE.md @AGENTS.md stub; audits token budget, cache safety, import-pattern compliance. Use when instruction files need alignment.
Creates AGENTS.md canonical and CLAUDE.md @AGENTS.md stub; audits token budget, cache safety, import-pattern compliance. Use when instruction files need alignment.
Use when installing or verifying this marketplace in Claude and Codex, aligning selected plugins, MCP settings, and Codex execution defaults.
Use when installing MCP packages and configuring Claude-side MCP registration, hooks, permissions, IDE extension mode, and migrations.
Use when installing MCP packages and configuring Claude-side MCP registration, hooks, permissions, IDE extension mode, and migrations.
Installs or updates Codex CLI and Claude Code. Use when CLI agents need installation or update.
Sets up linters, pre-commit hooks, and test infrastructure. Use when adding code quality tooling to a project.
Installs or updates Codex CLI and Claude Code. Use when CLI agents need installation or update.
Installs agents, configures MCP servers, aligns marketplace plugins, creates and audits instructions. Use after setup or when agents/MCP/plugins need alignment.
Installs agents, configures MCP servers, aligns marketplace plugins, creates and audits instructions. Use after setup or when agents/MCP/plugins need alignment.
Analyzes current or recent session for errors, inefficiencies, and improvement opportunities across skills, tools, hooks, and communication. Use after completing a task or periodically.
Profiles runtime performance with CPU, memory, and I/O metrics. Use when measuring bottlenecks before optimization.
Use when benchmarking hex-line MCP against Claude built-in tools with scenario manifests, activation checks, and diff-based correctness.
Bootstraps projects to production-ready structure. Use when creating new or transforming existing projects.
Sets up test infrastructure with Vitest, xUnit, and pytest. Use when adding testing frameworks and sample tests to a project.
Upgrades Python pip/poetry/pipenv dependencies with breaking change handling. Use when updating Python dependencies.
Verifies bootstrapped projects via build, test, and container health checks. Use when validating project setup completeness.
Use when validating optimization plans through the evaluation platform with mandatory research, parallel agent evidence, sequential merge, and bounded refinement.
Configures Husky, lint-staged, commitlint, and Python pre-commit hooks. Use when adding Git hook automation to a project.
Configures structured JSON logging with Serilog (.NET) or structlog (Python). Use when adding logging to backend projects.
Sets up security scanning for secrets and dependency vulnerabilities. Use when adding security infrastructure to a project.
Generates seed data from ORM schemas or entity definitions to any target format. Use when populating databases for development.
Configures ESLint, Prettier, Ruff, mypy, and .NET analyzers. Use when setting up linting and formatting for a project.
Creates backend docs (api_spec.md, database_schema.md). Use when project has backend API or database.
Sets up test infrastructure with Vitest, xUnit, and pytest. Use when adding testing frameworks and sample tests to a project.
Scans codebase for hardcoded secrets with severity classification and remediation guidance. Use when auditing a project for leaked credentials.
Checks compiler/linter errors, deprecation warnings, type errors, failed tests, build config issues. Use when auditing build health.
Upgrades .NET NuGet packages with breaking change handling. Use when updating .NET dependencies.
Scaffolds new or restructures existing projects to Clean Architecture. Use when setting up project structure.
Use when installing or verifying this marketplace in Claude and Codex, aligning selected plugins, MCP settings, and Codex execution defaults.
Configures ESLint, Prettier, Ruff, mypy, and .NET analyzers. Use when setting up linting and formatting for a project.
Generates GitHub Actions CI workflow configuration. Use when adding continuous integration to a project.
Generates Dockerfile and docker-compose configuration for multi-container development. Use when containerizing a project.
Sets up Docker, CI/CD, and environment configuration with auto-detection. Use when adding DevOps infrastructure to a project.
Removes platform-specific artifacts from Replit, StackBlitz, CodeSandbox, Glitch. Use when preparing exported projects for production.
Generates .NET Clean Architecture backend structure from entity definitions. Use when bootstrapping .NET backend projects.
Scaffolds new React projects or restructures monoliths to component-based architecture. Use when setting up frontend structure.
Bootstraps projects to production-ready structure. Use when creating new or transforming existing projects.
Configures CORS policy for development and production environments. Use when setting up cross-origin access for APIs.
Configures health check endpoints for Kubernetes readiness/liveness/startup probes. Use when deploying to Kubernetes.
Checks env var config sync, missing defaults, naming conventions, startup validation. Use when auditing environment configuration.
Discovers custom modules replaceable by OSS, evaluates alternatives (stars, license, CVE), generates migration plan. Use when reducing custom code.
Commits and pushes all changes (staged, unstaged, untracked) to remote. Use when you need a quick push of everything at once.
Coordinates project documentation creation with single context gathering and project type detection. Use when generating project docs subset.
Analyzes single pattern implementation, calculates compliance/completeness/quality scores, identifies gaps. Use when auditing a specific pattern.
Analyzes current or recent session for errors, inefficiencies, and improvement opportunities across skills, tools, hooks, and communication. Use after completing a task or periodically.
Configures environment variables and secrets protection. Use when setting up .env files and gitignore rules for a project.
Checks bootstrap initialization, graceful shutdown, resource cleanup, signal handling, liveness/readiness probes. Use when auditing app lifecycle.
Verifies claims in .md files (paths, versions, counts, configs, endpoints) against codebase, cross-checks contradictions. Use when auditing docs accuracy.
Checks structured logging, health checks, metrics collection, request tracing, log levels. Use when auditing observability.
Creates root documentation files (AGENTS.md, CLAUDE.md, docs/README.md, standards, principles). Use for initial project doc setup.
Checks unreachable code, unused imports/variables/functions, commented-out code, unsupported patterns. Use when auditing dead code.
Checks outdated packages, unused deps, reinvented wheels, CVE/CVSS vulnerability scan. Use when auditing dependencies.
Checks DRY, KISS/YAGNI, error handling, DI patterns. Use when auditing code principles compliance.
Checks unreachable code, unused imports/variables/functions, commented-out code, unsupported patterns. Use when auditing dead code.
Checks cyclomatic complexity, nesting, long methods, god classes, O(n2), N+1 queries, constants management. Use when auditing code quality.
Checks inline code documentation quality: WHY-not-WHAT, density, forbidden content, docstrings quality, actuality, legacy cleanup. Use when auditing comments and docstrings.
Checks document semantic content against SCOPE and project goals, coverage gaps, off-topic content, SSOT. Use when auditing documentation relevance.
Checks hierarchy, links, SSOT, compression, requirements compliance, freshness, legacy cleanup. Use when auditing documentation structure.
Plans automated tests (E2E/Integration/Unit) using Risk-Based Testing after manual testing. Use when Story needs a test task with prioritized scenarios.
Upgrades dependencies across all detected package managers. Use when updating npm, NuGet, or pip packages project-wide.
Analyzes application logs: classifies errors, checks log quality, maps stack traces to source. Use when logs need review after test runs or during development.
Replaces custom modules with OSS packages using atomic keep/discard testing. Use when migrating custom code to established libraries.
Reviews task implementation for quality, code standards, and test coverage. Use when task is in To Review. Sets task Done or To Rework.
Use when an evaluation run requires bounded iterative refinement with trace and cleanup evidence.
Modernizes codebase via OSS replacement and bundle optimization. Use when acting on audit findings to reduce custom code.
Checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Use when implementation tasks are Done and need quality scoring.
Executes optimization hypotheses with keep/discard testing loop. Use when applying validated performance improvements.
Upgrades dependencies across all detected package managers. Use when updating npm, NuGet, or pip packages project-wide.
Analyzes Story and builds optimal task plan (1-8 tasks), then routes to create or replan. Use when Story needs task breakdown or replanning.
RICE-scores Stories with market research and generates prioritization table. Use when Stories need business priority ranking for sprint planning.
Executes all test suites and reports results with coverage. Use when verifying that test infrastructure works after bootstrap.
Builds all detected projects and verifies successful compilation. Use when checking that a bootstrapped project compiles.
Sets up logging, error handling, CORS, health checks, and API docs. Use when adding cross-cutting concerns to backend projects.
Configures global exception handling middleware. Use when adding centralized error handling to .NET or Python backends.
Configures Swagger/OpenAPI documentation for backend APIs. Use when adding interactive API docs to a project.
Checks layer boundary violations, transaction boundaries, session ownership, cross-layer consistency. Use when auditing architecture layers.
Checks async races, thread safety, TOCTOU, deadlocks, blocking I/O, resource contention. Use when auditing concurrency safety.
Checks compiler/linter errors, deprecation warnings, type errors, failed tests, build config issues. Use when auditing build health.
Checks hardcoded secrets, SQL injection, XSS, insecure deps, input validation. Use when auditing security.
Discovers growth opportunities using Traffic-First KILL funnel. Use when searching for next product direction with validated demand.
Auto-fixes low-risk tech debt (unused imports, dead code, commented-out code) with >=90% confidence. Use when audit findings need safe automated cleanup.
Reduces JS/TS bundle size via tree-shaking, code splitting, and unused dependency removal. Use when optimizing frontend bundle size.
Builds dependency graph, detects cycles, validates boundary rules, calculates coupling metrics (Ca/Ce/I). Use when auditing dependency structure.
Researches competitive benchmarks and generates optimization hypotheses for identified bottlenecks. Use after profiling.
Multi-cycle performance optimization with profiling and bottleneck analysis. Use when optimizing application performance.
Checks hardcoded secrets, SQL injection, XSS, insecure deps, input validation. Use when auditing security.
Use when benchmarking hex-line MCP against Claude built-in tools with scenario manifests, activation checks, and diff-based correctness.
Extracts procedural content from project docs into slash commands. Use when docs contain deploy, test, or troubleshoot procedures.
Creates reference docs (ADRs, guides, manuals) for nontrivial tech stack choices. Use when project needs justified architecture decision records.
Decomposes scope into Epics, Stories, and RICE priorities. Use when user has project scope and wants full Agile breakdown.
Creates, replans, or appends 5-10 Stories per Epic with standards research and multi-epic routing. Use when Epic needs Story decomposition.
Creates or replans 3-7 Epics from scope using Decompose-First pattern. Use when initiative needs Epic-level breakdown or Epic scope changed.
Executes implementation tasks through Todo, In Progress, To Review. Use when task needs coding with KISS/YAGNI. Not for test tasks.
Orchestrates test planning pipeline: research, manual testing, automated test planning. Use when Story needs comprehensive test coverage planning.
Use when auditing the codebase through the evaluation platform with mandatory research, coordinated domain audit workers, and structured summaries.
Identifies missing tests for critical paths (money, security, data integrity, core flows). Use when auditing test coverage gaps.
Checks cyclomatic complexity, nesting, long methods, god classes, O(n2), N+1 queries, constants management. Use when auditing code quality.
Checks outdated packages, unused deps, reinvented wheels, CVE/CVSS vulnerability scan. Use when auditing dependencies.
Use when auditing architectural patterns through the evaluation platform with mandatory best-practice research, coordinated pattern workers, and structured summaries.
Checks test file organization, directory layout, test-to-source mapping, domain grouping, co-location. Use when auditing test structure.
Scores each test by Impact x Probability, returns KEEP/REVIEW/REMOVE decisions. Use when auditing test value and pruning low-value tests.
Analyzes single pattern implementation, calculates compliance/completeness/quality scores, identifies gaps. Use when auditing a specific pattern.
Checks file hygiene, ignore files, framework conventions, domain/layer organization, naming. Use when auditing project structure.
Checks env var config sync, missing defaults, naming conventions, startup validation. Use when auditing environment configuration.
Checks redundant fetches, N+1 loops, over-fetching, missing bulk operations, wrong caching scope. Use when auditing query efficiency.
Checks transaction scope, missing rollback handling, long-held transactions, trigger/notify interaction. Use when auditing transaction correctness.
Builds all detected projects and verifies successful compilation. Use when checking that a bootstrapped project compiles.
Profiles runtime performance with CPU, memory, and I/O metrics. Use when measuring bottlenecks before optimization.
Modernizes codebase via OSS replacement and bundle optimization. Use when acting on audit findings to reduce custom code.
Executes test tasks (label 'tests') through Todo to To Review with risk-based limits. Use for test task execution. Not for implementation tasks.
Fixes tasks in To Rework by applying reviewer feedback, then returns to To Review. Use when task was rejected during review.
Validates E2E coverage for critical paths (money, security, data integrity). Risk-based prioritization. Use when auditing E2E test coverage.
Researches competitive benchmarks and generates optimization hypotheses for identified bottlenecks. Use after profiling.
Multi-cycle performance optimization with profiling and bottleneck analysis. Use when optimizing application performance.
Builds and launches Docker containers with health verification. Use when validating that containerized services start correctly.
Configures Husky, lint-staged, commitlint, and Python pre-commit hooks. Use when adding Git hook automation to a project.
Checks session scope mismatch, missing cleanup, pool config, error path leaks, resource holding. Use when auditing resource lifecycle.
Checks blocking IO in async, unnecessary allocations, sync sleep, string concat in loops, redundant copies. Use when auditing runtime performance.
Checks layer leakage in method signatures, missing DTOs, entity leakage to API, inconsistent error contracts. Use when auditing API contracts.
Checks layer boundary violations, transaction boundaries, session ownership, cross-layer consistency. Use when auditing architecture layers.
Checks manual test scripts for harness adoption, golden files, fail-fast, config sourcing, idempotency. Use when auditing manual test quality.
Checks test isolation (API/DB/FS/Time/Network), determinism, flaky tests, order-dependency, anti-patterns. Use when auditing test isolation.
Checks bootstrap initialization, graceful shutdown, resource cleanup, signal handling, liveness/readiness probes. Use when auditing app lifecycle.
Checks structured logging, health checks, metrics collection, request tracing, log levels. Use when auditing observability.
Checks DRY, KISS/YAGNI, error handling, DI patterns. Use when auditing code principles compliance.
Performs manual testing of Story AC via executable bash scripts in tests/manual/. Use when Story implementation needs hands-on AC verification.
Runs existing test suite to catch regressions after implementation changes. Use when Story needs regression verification. No status changes.
Use when an evaluation run must merge research, findings, documentation, and repair outputs into one verified result.
Compares ideal plan vs existing tasks and applies KEEP/UPDATE/OBSOLETE/CREATE changes. Use when Story tasks need re-sync with updated requirements.
Creates implementation, refactoring, and test tasks from templates. Use when an approved task plan needs tasks created in Linear and kanban.
Replans Stories by comparing IDEAL vs existing (KEEP/UPDATE/OBSOLETE/CREATE). Use when Epic requirements changed and Stories need realignment.
Creates Story documents with 9-section structure and INVEST validation in Linear. Use when Epic has an IDEAL plan ready for Story generation.
Use when an evaluation run needs mandatory official-doc, MCP Ref, Context7, and current best-practice research with a structured research summary.
Creates core project docs (requirements, architecture, tech stack, patterns catalog). Use for any project regardless of type.
Builds and queries code knowledge graph for dependency analysis, references, implementations, and architecture overview. Use when starting work on unfamiliar codebase or before refactoring.
Use when removing Claude-side hex-line integration surfaces such as MCP registration, permissions, hooks, and output style.
Upgrades .NET NuGet packages with breaking change handling. Use when updating .NET dependencies.
Executes optimization hypotheses with keep/discard testing loop. Use when applying validated performance improvements.
Replaces custom modules with OSS packages using atomic keep/discard testing. Use when migrating custom code to established libraries.
Detects tests validating framework/library behavior instead of project code. Use when auditing test business logic focus.
Use when auditing project documentation through the evaluation platform with mandatory research, coordinated audit workers, and structured summaries.
Reduces JS/TS bundle size via tree-shaking, code splitting, and unused dependency removal. Use when optimizing frontend bundle size.
Use when auditing persistence and runtime performance through the evaluation platform with mandatory research, coordinated data-layer workers, and structured summaries.
Checks async races, thread safety, TOCTOU, deadlocks, blocking I/O, resource contention. Use when auditing concurrency safety.
Builds dependency graph, detects cycles, validates boundary rules, calculates coupling metrics (Ca/Ce/I). Use when auditing dependency structure.
Executes all test suites and reports results with coverage. Use when verifying that test infrastructure works after bootstrap.
Researches real-world problems, competitor solutions, and customer complaints for a feature domain. Use before test planning to ground tests in actual user pain points.
Discovers custom modules replaceable by OSS, evaluates alternatives (stars, license, CVE), generates migration plan. Use when reducing custom code.
Use when auditing the test surface through the evaluation platform with mandatory research, coordinated test audit workers, and structured summaries.
Upgrades npm/yarn/pnpm dependencies with breaking change handling. Use when updating JavaScript/TypeScript dependencies.
Upgrades Python pip/poetry/pipenv dependencies with breaking change handling. Use when updating Python dependencies.
Commits and pushes all changes (staged, unstaged, untracked) to remote. Use when you need a quick push of everything at once.
Creates infrastructure.md and runbook.md (Docker-conditional). Use for DevOps documentation in any project.
Generates .NET Clean Architecture backend structure from entity definitions. Use when bootstrapping .NET backend projects.
Generates GitHub Actions CI workflow configuration. Use when adding continuous integration to a project.
Configures environment variables and secrets protection. Use when setting up .env files and gitignore rules for a project.
Generates Dockerfile and docker-compose configuration for multi-container development. Use when containerizing a project.
Removes platform-specific artifacts from Replit, StackBlitz, CodeSandbox, Glitch. Use when preparing exported projects for production.
Scaffolds new React projects or restructures monoliths to component-based architecture. Use when setting up frontend structure.
Creates design_guidelines.md with WCAG 2.1 compliance and design system docs. Use when project has a frontend.
Scaffolds new or restructures existing projects to Clean Architecture. Use when setting up project structure.
Creates task management docs (kanban board, workflow rules) with Linear integration. Use when setting up task tracking for a project.
Creates test documentation (testing-strategy.md, tests/README.md) with Risk-Based Testing philosophy. Use when setting up test strategy for a project.
Responds to unanswered GitHub discussions and issues with codebase-informed replies. Use when clearing community question backlog.
Composes and publishes announcements to GitHub Discussions. Use when sharing releases, updates, or news with the community.
Produces prioritized triage report from open GitHub issues, PRs, and discussions. Use when reviewing community backlog.
Analyzes community health and delegates engagement tasks. Use when managing GitHub issues, discussions, and announcements.
Verifies bootstrapped projects via build, test, and container health checks. Use when validating project setup completeness.
Configures Swagger/OpenAPI documentation for backend APIs. Use when adding interactive API docs to a project.
Configures CORS policy for development and production environments. Use when setting up cross-origin access for APIs.
Sets up security scanning for secrets and dependency vulnerabilities. Use when adding security infrastructure to a project.
Sets up Docker, CI/CD, and environment configuration with auto-detection. Use when adding DevOps infrastructure to a project.
Scans codebase for hardcoded secrets with severity classification and remediation guidance. Use when auditing a project for leaked credentials.
Sets up logging, error handling, CORS, health checks, and API docs. Use when adding cross-cutting concerns to backend projects.
Configures structured JSON logging with Serilog (.NET) or structlog (Python). Use when adding logging to backend projects.
Configures global exception handling middleware. Use when adding centralized error handling to .NET or Python backends.
Configures health check endpoints for Kubernetes readiness/liveness/startup probes. Use when deploying to Kubernetes.
Launches RFC and debate discussions on GitHub. Use when proposing changes that need community input or voting.
Sets up linters, pre-commit hooks, and test infrastructure. Use when adding code quality tooling to a project.
Generates seed data from ORM schemas or entity definitions to any target format. Use when populating databases for development.