agent-dispatcher

In the author's own words, from each skill's SKILL.md — showing the first 30 of 80 files.

• agent-dispatcher

  Handle requested Agent Dispatcher work with direct execution or prepared specialist guidance. Includes named roles, context inspection and controls.

  skills/agent-dispatcher/SKILL.md on GitHub (opens in a new tab)

• agent-design

  Scope an agent or subagent before it is built — the one job it owns, the smallest tool set that closes that job, what it must never do, and the evidence it has to return. Use when adding an agent, subagent or automated role to a system, when deciding which tools it gets, when an existing agent loops, over-reaches or reports work it did not do, or when reviewing someone else's agent design. Not fo…

  skills/ai/agent-design/SKILL.md on GitHub (opens in a new tab)

• agent-evals

  Build an eval suite that can actually detect a regression — cases pulled from real traffic, graders that check properties rather than vibes, a recorded baseline, and per-case diffs in both directions. Use before claiming a prompt, model or agent change is an improvement, when agent behaviour must not regress, or when someone reports "it seems better" after eyeballing a handful of outputs. Not for…

  skills/ai/agent-evals/SKILL.md on GitHub (opens in a new tab)

• context-engineering

  Decide what actually occupies the model's window — progressive disclosure through an index, retrieval versus inlining, what compaction must preserve, and what loading everything costs. Use when a prompt or agent pulls in many files, docs or tool transcripts, when quality decays over a long session, when choosing between fetching at runtime and pasting up front, or when a context has to be trimmed…

  skills/ai/context-engineering/SKILL.md on GitHub (opens in a new tab)

• llm-observability

  See what an agent actually did — one trace per run with nested model, tool and retrieval spans, token and latency accounted per step, and failures clustered by mechanism instead of read one at a time. Use when an agent misbehaves in ways you cannot reproduce, when cost or latency is unexplained, when "it sometimes fails" is the whole bug report, or before writing evals when you do not yet know wh…

  skills/ai/llm-observability/SKILL.md on GitHub (opens in a new tab)

• mcp-design

  Build an MCP server, or bring an existing one into a project — choosing the transport, deciding which tools, resources and prompts to expose, keeping reads separate from writes, handling auth and credentials, and defining what failure looks like to the model. Use when writing an MCP server, wrapping an internal system as one, or evaluating a third-party server before wiring it in. Not for designi…

  skills/ai/mcp-design/SKILL.md on GitHub (opens in a new tab)

• memory-design

  Decide what an agent should remember, which layer holds it, who it is scoped to, and how a stale or contradicted memory is detected and retired. Use when an agent forgets something across sessions, when a memory or persistent-context feature is being designed, or when stored memories have grown noisy, wrong, or are leaking between users. Not for retrieval over a document corpus, not for prompt or…

  skills/ai/memory-design/SKILL.md on GitHub (opens in a new tab)

• model-routing

  Pick a model per job and degrade sensibly when one fails — a quality bar per call site, candidates compared on the same task set, a readable routing rule, and an explicit retry-versus-fallback path with pinned model ids. Use when cost or latency has become a problem, when adding a cheaper or larger model to an existing system, or when a fallback fires silently and quality drops without anyone not…

  skills/ai/model-routing/SKILL.md on GitHub (opens in a new tab)

• prompt-engineering

  Write or revise a prompt so it holds up — output contract, instruction placement, examples that earn their place, an escape hatch for bad input — and measure the change against a saved set of cases instead of one good-looking run. Use when a prompt is being authored or patched, when output is inconsistent or the wrong shape, when a model or version changes, or when someone reports a prompt as fix…

  skills/ai/prompt-engineering/SKILL.md on GitHub (opens in a new tab)

• prompt-injection-defense

  Treat everything an agent reads but did not author as data rather than instructions — an explicit trust boundary, a tool set fixed before content is read, consequential calls gated on the user, and destinations that cannot be chosen by the content. Use when an agent reads web pages, retrieved documents, emails, tool results, file contents or another agent's output and can also take actions, when…

  skills/ai/prompt-injection-defense/SKILL.md on GitHub (opens in a new tab)

• retrieval-rag

  Build and fix retrieval that actually returns the right passage — structure-aware chunking, one pinned embedding model, lexical plus vector search fused, reranking, and a recall measurement that is run separately from the generator. Use when a RAG system answers wrong or vaguely, when an index is being designed or reindexed, or when someone proposes a prompt change to fix what is really a retriev…

  skills/ai/retrieval-rag/SKILL.md on GitHub (opens in a new tab)

• structured-output

  Get parseable, trustworthy structured results out of a model — schema design, the enforcement mechanism the provider actually offers, validation at the boundary, bounded retry that feeds the error back, and recognising where a schema stops buying correctness. Use when a model's output feeds code rather than a human, when parsing keeps failing or fields come back plausible-but-wrong, or when desig…

  skills/ai/structured-output/SKILL.md on GitHub (opens in a new tab)

• tool-design

  Design the tools a model calls — names, parameter shapes, what a result returns, and error text written as an instruction the model can act on. Use when adding or reshaping a tool or function an LLM invokes, when an agent keeps calling the wrong tool or passing malformed arguments, or when reviewing a tool surface someone else defined. Not for building the MCP server that hosts the tools (mcp-des…

  skills/ai/tool-design/SKILL.md on GitHub (opens in a new tab)

• api-contract-verification

  Prove an API integration actually works by executing it — success path, documented failure paths, auth failure — and leave behind a contract test that catches the next break. Use before reporting any endpoint, client or third-party integration as working, when asked whether an integration is verified, or when checking someone else's integration work. Not for load or performance testing, not for r…

  skills/backend/api-contract-verification/SKILL.md on GitHub (opens in a new tab)

• api-design

  Design or change an HTTP API — resources, verbs, status codes, one error shape, pagination, versioning, and an OpenAPI description that cannot drift from the handlers. Use when adding or reshaping endpoints, when asked what a response should return, or when reviewing whether a change to a published API breaks its consumers. Not for choosing between REST, GraphQL and RPC, not for database schema d…

  skills/backend/api-design/SKILL.md on GitHub (opens in a new tab)

• authentication

  Establish who the caller is — session cookies, bearer tokens, refresh, and OAuth/OIDC flows — and put each where it belongs. Use when adding or changing login, logout, signup, session handling, token issuance or refresh, an identity-provider integration, or when a request arrives with a credential nobody validates. Not for deciding what an authenticated caller may then do (that is authorization),…

  skills/backend/authentication/SKILL.md on GitHub (opens in a new tab)

• authorization

  Decide what an authenticated caller may do — pick the permission model, put the check at one enforcement point close to the data, and default to deny. Use when adding roles or permissions, scoping data per tenant or per owner, building an admin-only path, reviewing an endpoint that trusts a client-supplied id, or when someone reports seeing data that is not theirs. Not for establishing identity (…

  skills/backend/authorization/SKILL.md on GitHub (opens in a new tab)

• background-jobs

  Design queued and scheduled work so it survives duplicates, retries, crashes and restarts — job contract, idempotency, transactional enqueue, backoff, dead letters, leases and the ordering guarantees you actually have. Use when moving work off a request path, adding a worker or cron, or debugging a job that ran twice, never ran, ran out of order, or is stuck retrying forever. Not for in-request a…

  skills/backend/background-jobs/SKILL.md on GitHub (opens in a new tab)

• caching

  Decide what to cache, at which layer, for how long, and how it gets invalidated — before any cache is added. Use when someone proposes caching to make a read path faster, when stale or cross-user data is suspected, when adding a TTL or a Redis/CDN layer, or when reviewing a change that introduces one. Not for fixing a slow query or an N+1 (do that first — a cache over a bad query hides it), and n…

  skills/backend/caching/SKILL.md on GitHub (opens in a new tab)

• idempotency-and-retries

  Make an operation safe to repeat — idempotency keys and their storage, what a replay returns, retry policy with backoff and jitter, and how to reconcile after a timeout whose outcome is unknown. Use when an operation has an external side effect (a charge, an email, a provisioning call), when a caller needs to retry safely, or when duplicates have already appeared in production. Not for webhook re…

  skills/backend/idempotency-and-retries/SKILL.md on GitHub (opens in a new tab)

• webhooks

  Receive or send HTTP webhooks correctly — signature verification on the raw body, fast acknowledgement, deduplication, out-of-order handling, retry and dead-letter behaviour, and the delivery contract a consumer needs. Use when adding or debugging a webhook endpoint, when integrating a provider's events, or when your own service has to notify others of changes. Not for internal queue or event-bus…

  skills/backend/webhooks/SKILL.md on GitHub (opens in a new tab)

• data-integrity

  Keep data correct over time — write the invariants down, push each one to the lowest layer that can enforce it, cover the rest with reconciliation queries, and detect drift before a user reports it. Use when deciding where a rule should be enforced, auditing a schema whose rules live only in application code, building reconciliation or drift checks, or investigating data that looks wrong. Not for…

  skills/database/data-integrity/SKILL.md on GitHub (opens in a new tab)

• data-pipelines

  Build and repair batch and streaming pipelines that can be run twice without lying — lineage, event-time windowing, late arrivals, re-runnable writes and bounded backfills. Use when writing or fixing a pipeline, scheduled transform or job that produces data someone reads, when a run dropped or duplicated rows, or when planning a backfill. Not for designing the destination schema or its migrations…

  skills/database/data-pipelines/SKILL.md on GitHub (opens in a new tab)

• data-quality

  Decide what must be true of a dataset and where that assertion belongs — freshness against event time, volume floors and bands, distribution and referential checks, source reconciliation, and whether it should be a schema constraint, a blocking publish gate or an alert. Use when adding or reviewing data checks, when a wrong number reached a consumer and nothing caught it, or when a check fires so…

  skills/database/data-quality/SKILL.md on GitHub (opens in a new tab)

• database-migration-verification

  Prove a migration did what it claimed — before/after row counts, column checksums, constraint and index state, invariant queries, an exercised application read path, and a rehearsed rollback. Use after a migration has been applied to any environment and before anyone reports it as working, or when reviewing someone else's claim that a migration succeeded. Not for planning or sequencing the migrat…

  skills/database/database-migration-verification/SKILL.md on GitHub (opens in a new tab)

• migrations

  Change a live schema without breaking the application on it — expand/contract sequencing, lock-safe DDL, batched backfills, and a rollback that is actually reachable. Use when writing, reviewing or sequencing a migration that will run against a database holding real data with live readers. Not for designing a schema from scratch, not for proving afterwards that a migration did what it claimed (th…

  skills/database/migrations/SKILL.md on GitHub (opens in a new tab)

• postgres

  Postgres behaviour worth checking before relying on it — type choices, index kinds and their costs, reading EXPLAIN output, isolation levels and lock behaviour during DDL, and row-level security. Use when the project runs on Postgres (including Postgres-backed services) and a decision depends on what the engine actually does: picking a column type, adding an index, changing isolation, or writing…

  skills/database/postgres/SKILL.md on GitHub (opens in a new tab)

• query-optimization

  Make one slow query fast without guessing — capture the plan, find where the time actually goes, change one thing, and measure again on comparable data. Use when a query, endpoint or report is slow and the database is the suspect, when a plan needs reading, or when someone proposes an index with no evidence. Not for modelling decisions about tables and constraints, not an engine feature reference…

  skills/database/query-optimization/SKILL.md on GitHub (opens in a new tab)

• schema-design

  Turn what a system must guarantee into tables, keys and constraints — normalization judgement, nullability, foreign key behaviour, and naming that survives. Use when designing new tables, reviewing ORM models or a migration's DDL, or when a bug reduces to "the database allowed a row that should be impossible". Not for tuning a slow query, not for engine-specific syntax and features, and not for w…

  skills/database/schema-design/SKILL.md on GitHub (opens in a new tab)

• accessibility-verification

  Prove an accessibility claim instead of asserting it — automated scan plus the keyboard, focus, zoom and screen-reader passes a scanner structurally cannot make. Fires before anyone says a screen is accessible or WCAG AA, when signing off UI work, or when an audit result needs checking. Not for making the fixes (accessibility), and it never upgrades a clean scan into a conformance claim.

  skills/design/accessibility-verification/SKILL.md on GitHub (opens in a new tab)

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