Hold a daily standup with the named Herdr agents and print a table the operator can find while scrolling back through a long session: ask each idle worker for four lines (DONE / PLAN / BLOCKED / REPORT), fill the busy ones from the round log, and render a banner-topped fixed-width block plus a Markdown record. Use when the user wants a standup, a daily status round, a summary of what each agent is doing, "what is everyone working on", or a status table for the team. Requires HERDR_ENV=1.

Run Herdr rounds with on-demand specialists, model tiers, bounded briefs, report verification, and release gates. Use for requests to dispatch the Herdr team, balance worker usage, collect reports, run or retrieve retrospectives, catch up on outstanding user attention, curate team lessons, or save and resume lead handoffs. Live rounds require HERDR_ENV; saved memory and attention work offline. Other standalone tasks skip this skill.

Bootstrap a consumer repo onto gamussa/coding-policy: install the plugin at `latest`, gitignore tessl's generated artifacts, scaffold the Codex policy-review workflow plus the Copilot lane charter, set the CODEX_AUTH_JSON secret, then commit and ship via the release skill. Use when the user wants to add, install, enable, scaffold, set up, wire up, or enroll coding-policy / an automated policy review / a PR reviewer in a repo. Also use to upgrade or refresh the reviewer files in a repo that already has them (override mode: "upgrade", "update", "refresh", "--override").

Reviews repositories, pull requests, diffs, and agent-generated code for implementation integrity failures: reward hacking, fake completion, defensive theater, test manipulation, architectural bypasses, weakened guarantees, and misleading abstractions. Use whenever the user asks for an integrity review, adversarial review, reward-hacking review, fake implementation review, shortcut audit, or verification that an implementation genuinely satisfies its stated contract.

Use when the user asks to write unit tests, generate a test suite, or migrate/convert Jest or Vitest tests to Themis in Node.js/TypeScript repos. Produces Themis-native tests, runs validation commands, and applies Themis migration workflows.

enforces engineering-governance checks before code changes that may be unnecessary, risky, architectural, or scope-widening. use when the user asks whether to refactor, clean up, redesign, choose a next development step, review a proposed implementation, evaluate architectural consistency, review a pull request, or prevent development drift. do not use as the primary implementation skill for routine debugging, bug fixes, feature coding, or language-specific coding unless a no-op, minimal-diff, or architecture-conflict judgment is needed.

Manage Things 3 tasks on macOS -- view lists, create tasks with deadlines and tags, complete tasks, move between projects, set due dates, search, and organize. This skill should be used when the user mentions Things 3, wants to manage tasks or to-dos, asks about their inbox, today, upcoming, or someday tasks, wants to create, complete, move, or delete tasks, discusses projects or task management, or says things like 'add a task', 'show my inbox', 'what do I need to do today', 'mark it done', 'my to-do list'.

Cypress E2E testing patterns -- commands, selectors, network stubbing, auth caching, time control, test isolation, and best practices. Use when building or reviewing E2E tests with Cypress, when setting up browser testing, or when debugging flaky Cypress tests.

Go API testing patterns that catch real bugs. Covers httptest server setup, table-driven tests with subtests, test helpers, middleware testing, dependency injection with interfaces, database setup/teardown, parallel tests, testify assertions, and golden files. Triggers when writing tests for any Go HTTP API, adding test coverage, or building a new API that needs tests.

Reference catalog of the eight flake patterns - async/timing, test ordering, shared parallel state, resource leaks, network, locator drift, environment variance, randomness - with detection heuristics, remediation per pattern, and the concrete code-level fixes: replacing fixed sleeps with framework auto-waits, isolating state in beforeEach fixtures, per-worker DB schemas via workerIndex, try/finally teardown, mocking network + clock at the boundary, stable role-based locators, TZ pinning, and RNG seeding. Use when triaging an unknown flake to identify the category before bisecting, or when a classified flake needs the specific code change to apply.

Use when reviewing iOS or iPadOS apps for App Store submission, TestFlight readiness, rejection recovery, Resolution Center replies, Guideline 4.3 similarity, or product craft. Includes iOS 27 compatibility, SDK and deployment gates, scene lifecycle, iPhone Duo, Apple Intelligence, Foundation Models, Siri/App Intents, privacy, subscriptions, accessibility, new App Store assets, and Apple design and Human Interface Guidelines audits of native interaction, motion, gestures, materials, haptics, and iPad adaptation. Applies to Xcode, Expo, React Native, and Flutter projects, supplied rejections or metadata, and requests such as "review my app" or "will Apple approve this".

Write correct Flask tests that avoid common pitfalls. Covers app factory with test config, application context for test_client, pytest fixtures in conftest.py, database isolation with transactions, testing file uploads, testing error handlers, testing with authentication, mock.patch placement, and the essential test patterns that catch real bugs. Use when writing or reviewing Flask test suites.

SQLite best practices that must be applied by default in every Go application using database/sql with SQLite. Covers connection setup with WAL mode, foreign_keys, busy_timeout, pool settings (SetMaxOpenConns), modernc.org/sqlite (pure Go, no CGO), context-aware queries, transactions, migration patterns, prepared statements, and the Scanner interface. Always apply these patterns when creating or modifying any Go application that uses SQLite.

Create, configure, and deploy PubNub Functions 2.0 event handlers, triggers, and serverless endpoints. Use when building real-time message transformations, PubNub modules, webhook integrations, or edge data processing.

Derives human-readable manual test cases from stateful behavior: identify states, events, transitions, and guard conditions, draw the state table including invalid (empty-cell) transitions, choose a coverage level (all states, valid transitions / 0-switch, transition pairs / 1-switch per Chow, all transitions including invalid ones), then derive one test case per coverage item as an event sequence with per-step expected states (ISTQB CTFL v4.0 section 4.2.4). A deep single-technique walkthrough rather than a broad multi-lens case matrix; the output is manual step/expected cases rather than parameterized test code, and it covers how cases are derived rather than how a case record is structured. Use for lifecycle entities (accounts, orders, subscriptions), workflows, and UI wizards where the response to an event depends on the current state.

Fixes test data that breaks tests - factory values in a shape the code under test rejects (a phone number that is not E.164), fixtures that only pass when the whole suite runs in order, and random values that make an assertion pass or fail depending on the run. Authors test-data factories with Faker: the Python `faker` library, the `@faker-js/faker` JS port, and the `faker-ruby` gem - install per language, the provider catalogue (person / internet / location / date / finance / lorem), locale selection and multi-locale mode, and seed-based determinism for reproducible runs. Scope is generating fresh values for tests that start from nothing, not replacing values inside a dataset that already holds real records - that goes to pii-masking-pipeline-builder. Use when fixtures need realistic values, a stable shape, or a fixed seed.

Decides what kind of failure a red CI test is before anyone starts fixing it. Extracts seven failure signals from the runner output, stack trace, run history, and environment metadata, then walks an ordered first-match-wins rule set to exactly one verdict: flaky-known, environment-drift, defect, timeout, flaky-pre-incident, or flake-of-unknown-cause. Emits the verdict together with the alternatives that were rejected and the specific condition each one failed, so the triage decision is auditable rather than asserted. Use when a test has just gone red and the next action depends on whether the cause is a product defect, a non-deterministic test, or drifted infrastructure.

Flask patterns -- application factory, blueprints, error handlers, extensions, request lifecycle, configuration, logging, CLI commands, and project structure. Use when building or reviewing Flask APIs, setting up a new Flask project, migrating from a single-file app to a structured project, or choosing between Flask patterns.