Skills
The open registry for AI agent skills — structured prompts and workflows with recommended models, example prompts, and compatible tools.
Skills
167
Categories
9
Compatible tools
5
Contributors
1
Showing 22–42 of 100 skills
Helps process a busy inbox quickly. Categorizes messages by urgency and type, extracts action items and deadlines, drafts short reply options, and proposes an order to handle them. Summarizes long threads into the decision needed and flags anything sensitive or requiring escalation, so you can clear the inbox with fewer decisions.
Writes conversion-focused ad copy for search, social, and display. Crafts headlines and descriptions within platform character limits, leads with a clear benefit and hook, matches message to audience and funnel stage, and produces multiple variants for A/B testing. Keeps claims honest and includes a strong, specific call to action.
Explains what a SQL query does in plain language and how it executes. Breaks down joins, subqueries, CTEs, and window functions step by step, describes the result set, reads EXPLAIN/EXPLAIN ANALYZE output to identify slow scans and missing indexes, and flags correctness pitfalls. Helps developers understand, review, and trust unfamiliar SQL.
Helps turn a game concept into a structured game design document. Captures the core loop, mechanics, progression, economy, controls, level structure, art and audio direction, and target platform and audience. Keeps scope realistic, flags dependencies and risks, and produces a living GDD that a small team can build from.
Decodes and reviews JSON Web Tokens and their surrounding auth flow for correctness and security. Explains header and claims, checks algorithm and key handling, validates expiration and audience/issuer claims, and flags common pitfalls such as the alg:none attack, weak secrets, missing validation, and over-long token lifetimes. Never treats token contents as trusted secrets to echo back.
Designs surveys that produce reliable, unbiased data. Turns research goals into clear questions, chooses appropriate scales and response types, avoids leading and double-barreled wording, orders questions to reduce bias, and plans screening and branching logic. Outputs a ready-to-field questionnaire with an analysis plan for each question.
Builds structured competitive analyses from public information. Maps competitors across positioning, pricing, features, target segments, and go-to-market motion; produces feature-comparison matrices and SWOT summaries; and highlights differentiation gaps and opportunities. Emphasizes citing sources and separating verified facts from inference.
Reviews claims in a document for accuracy and verifiability. Extracts discrete factual statements, rates each as supported, unsupported, or needs-verification, flags logical inconsistencies and unsourced numbers, and suggests what evidence would confirm or refute each claim. Designed to reduce hallucinated or outdated facts before publishing.
Helps make and document structured decisions. Elicits the options and the criteria that matter, assigns weights, scores each option, computes a weighted result, and runs a quick sensitivity check to show how robust the recommendation is. Produces a clear matrix plus a short written rationale suitable for an ADR or decision log.
Designs and implements rate limiting for APIs and services. Recommends an algorithm (token bucket, leaky bucket, fixed or sliding window) for the use case, defines per-key and per-endpoint limits, plans distributed enforcement with Redis, and specifies response headers and 429 handling with retry-after. Produces a design plus reference implementation.
Reviews applications and data flows for common privacy-regulation obligations (GDPR, CCPA/CPRA). Maps what personal data is collected, where it flows, and how long it is retained; checks for lawful basis, consent handling, data-subject rights, and third-party sharing; and produces a prioritized remediation list. Provides engineering guidance, not legal advice.
Turns a messy list of tasks into a ranked, actionable plan. Applies a chosen framework (Eisenhower urgent/important, RICE, MoSCoW, or value/effort) consistently, surfaces dependencies and quick wins, groups work into a realistic today/this-week plan, and explains the ranking so the user can adjust the weighting.
Turns merged pull requests, commits, and issue references into clear, audience-appropriate release notes. Groups changes into features, fixes, and breaking changes, translates technical detail into user-facing value, and produces both a concise highlights section and a complete changelog.
Builds cross-browser extensions on Manifest V3 with background service workers, content scripts, popup and options UIs, and message passing. Covers permissions scoping, storage sync, context menus, and store submission requirements for Chrome, Edge, and Firefox. Emphasizes least-privilege permissions and secure content-script isolation.
Defines data contracts between producers and consumers to prevent breaking changes in pipelines. Covers schema definitions, semantic types, freshness and quality SLAs, ownership, versioning, and backward/forward compatibility rules. Generates contract specs (e.g., ODCS-style) and CI checks that fail builds when a producer violates the contract.
Modernizes legacy codebases incrementally and safely. Establishes characterization tests to lock in current behavior, then applies the strangler-fig pattern, dependency updates, and idiomatic refactors in small verifiable steps, producing a migration plan that avoids big-bang rewrites.
Builds robust webhook producers and consumers. Covers signature verification, idempotency keys, retry with exponential backoff, dead-letter handling, event ordering, and replay endpoints, and generates handler code plus tests so integrations survive duplicates and outages.
Generates and validates Software Bills of Materials in CycloneDX or SPDX formats. Covers dependency inventory, transitive resolution, license and vulnerability annotation, VEX statements, container image SBOMs, and CI integration for supply-chain compliance. Helps teams meet regulatory requirements and track what is actually shipped.
Designs data quality checks for tables, pipelines, and warehouses. Generates expectation suites covering schema conformance, null and uniqueness constraints, referential integrity, freshness, and statistical drift, then wires them into pipelines so bad data is caught before it reaches dashboards or models.
Designs recommendation systems end to end: candidate generation, ranking, and re-ranking. Covers collaborative filtering, content-based and embedding retrieval, two-tower models, cold-start strategies, feature stores, offline/online evaluation (NDCG, recall@k), and feedback loops. Produces an architecture and evaluation plan tailored to the product.
Turns strategy into well-formed Objectives and Key Results. Coaches on ambitious yet measurable objectives, outcome-based (not output-based) key results, leading vs lagging indicators, alignment across teams, and quarterly cadence with check-ins and scoring. Flags common anti-patterns like task lists disguised as OKRs.
Skills vs MCP servers
what's the difference?Skillsthe “what to do”
A skillA reusable, structured prompt/workflow with recommended models, an example prompt, and compatible tools. packages know-how — instructions, an example promptA ready-to-use prompt template that demonstrates how to invoke the skill., and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.
MCP serversthe “how to connect”
An MCP serverModel Context Protocol server — a standard way to expose tools, resources, and prompts to AI agents and IDEs. gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transportHow the client talks to the server: stdio (local process), SSE, or HTTP streaming.. MCP adds connections and actions, not task instructions.
Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.
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