Claude Code Skills · page 53

Write a local development environment setup guide for a service or project — covering prerequisites, repository setup, environment variables, local service dependencies, database seeding, running the service, running tests, common gotchas, IDE recommendations, and first-contribution checklist. Use when asked to write a dev setup guide, create onboarding documentation for engineers, document local environment setup, or write a getting-started guide for a codebase. Produces a complete setup guide that a new engineer can follow from zero to running tests in under 30 minutes, with a troubleshooting section for the most common setup failures.

Design a microservices decomposition for a monolith or new system, defining service boundaries, ownership, communication patterns, and migration plan. Use when asked to decompose a monolith, define service boundaries, design a microservices architecture, or plan a strangler-fig migration. Produces a bounded context map, service inventory table, communication pattern decisions, data ownership matrix, migration roadmap, and risk register.

Write a monitoring setup guide for a service — defining what to measure, how to alert on it, and how to build the observability stack covering the four golden signals, business metrics, log strategy, distributed tracing, alerting rules, dashboard layout, and observability debt. Use when asked to set up monitoring for a service, define alerting strategy, write an observability plan, create a dashboard specification, or document logging standards for a team. Produces a metric definitions table, alert rules specification, dashboard layout wireframe, log schema, tracing setup checklist, and monitoring gap analysis.

Write an on-call runbook for a service — covering alert definitions, escalation paths, common incident responses, and on-call handoff procedures. Use when asked to write an on-call guide, create alert runbooks, document escalation procedures, or prepare an on-call handoff document. Produces a structured on-call runbook with per-alert response procedures, escalation matrix, diagnostic commands, and handoff template.

Define and document performance budgets for a web service or application. Use when asked to set performance targets, define SLOs for latency or throughput, establish Core Web Vitals targets, create a performance baseline, or document performance regression policy. Produces a structured performance budget covering key user journeys, Core Web Vitals, backend latency SLOs, measurement tooling, CI enforcement, and breach response process.

Write a clear, structured pull request description from a git diff, branch summary, or commit list. Use when asked to write a PR description, draft a pull request, or document code changes. Produces a description with summary, motivation, changes made, testing steps, and reviewer guidance.

Write an engineering RFC (Request for Comments) for a technical decision, architectural change, or significant implementation approach. Use when asked to write an RFC, document a technical proposal, create a design doc, write an architecture decision for review, or produce a technical specification for team feedback. Produces a complete RFC document covering problem statement, motivation, proposed solution, alternatives rejected, implementation plan, migration plan, security and performance implications, observability changes, rollout plan, and open questions.

Write an operational runbook for a service, incident type, or deployment procedure. Use when asked to write a runbook, create an ops guide, document an operational procedure, or prepare an incident response playbook. Produces a runbook with overview, prerequisites, step-by-step procedures, rollback steps, troubleshooting table, and escalation paths.

Write a STRIDE-based threat model for a service or feature. Use when asked to produce a threat model, document security risks, identify attack vectors, assess a service's security posture, or prepare for a security design review. Produces a structured threat model covering assets, trust boundaries, STRIDE threat enumeration per component, risk scores, mitigation controls, and residual risk sign-off.

Write a service catalog entry for a microservice or internal platform service — covering service identity, purpose, architecture context, SLAs, API contract summary, data classification, dependencies, operational runbooks, and known limitations. Use when asked to document a service for an internal developer portal, write a service README for a platform catalog, create a service overview page, or onboard a new service to a service registry. Produces a complete service catalog entry suitable for an internal developer portal or wiki.

Define Service Level Objectives (SLOs) and an error budget policy for a service. Use when asked to write SLOs, define SLIs, calculate an error budget, set reliability targets, or create an error budget policy. Produces a complete SLO document with SLI definitions, target calculation, error budget policy, burn rate alerts, and review cadence.

Assesses pre-launch readiness across every function and produces an explicit Go / Conditional Go / No-Go recommendation. Use when preparing for any product or feature launch, running a pre-launch review, or determining whether a release is safe to ship. Produces a function-by-function readiness status, a ranked blockers list with owners and deadlines, a risk register, and a clearly reasoned launch recommendation.

Stress-test a plan, strategy, PRD, or launch by simulating hostile expert personas who attack it from every angle. Use when asked to red-team, stress-test, pre-mortem, pressure-test, play devil's advocate, or find the blind spots in a plan before committing. Produces a per-persona critique, a ranked list of the most dangerous risks, a pre-mortem, and the specific changes that would most strengthen the plan.

Explain what a piece of code does in plain English, at the depth the reader needs. Use when asked to explain code, walk through a function, understand an unfamiliar snippet, or onboard to a file. Produces a one-line summary, a step-by-step walkthrough, the non-obvious parts called out, and any bugs or smells spotted along the way.

Turn one piece of content into a full multi-platform pack — X/Twitter thread, LinkedIn post, newsletter section, Instagram carousel, and a short-form video script — each rewritten natively for its platform, not copy-pasted. Use when asked to repurpose content, atomize a blog post or video, turn one idea into many posts, or get more mileage from a piece. Produces ready-to-post drafts per platform with hooks, formatting, and CTAs tuned to each.

Define a creator's brand foundation — niche, audience, positioning, content pillars, voice/tone, and bio — so every post is consistent and on-brand. Use when asked to define a creator brand, find a niche, set content pillars, write a voice guide, craft a bio, or build a brand kit for a personal brand or channel. Produces a reusable one-page brand kit that other content skills can read so output sounds like you, every time.

Build a creator's sponsorship media kit and brand-deal outreach — the one-pager brands ask for, plus a pitch email and a rate card. Use when asked to make a media kit, pitch a brand, land a sponsorship, write a brand-deal email, or set creator rates. Produces a structured media kit (audience, stats, offerings, past work), a personalised outreach email, and a defensible rate card. The creator side of a sponsorship — distinct from a brand briefing a creator.

Generate scroll-stopping hooks — the first line of a post, thread, video, or email that decides whether anyone keeps reading. Use when asked to write a hook, an opener, a first line, a thread starter, a video cold-open, or to make something more clickable. Produces multiple distinct hook options across proven angles (curiosity, contrarian, result, story, stakes), each labelled with why it works and which platform it fits.

Write a full creator newsletter issue — subject line, preview text, hook, body with a clear takeaway, and a CTA — in the writer's voice, for Substack, beehiiv, ConvertKit, or email. Use when asked to write a newsletter, an email issue, a Substack post, or to turn notes/a topic into a sendable newsletter. Produces a ready-to-send issue with subject-line options and a skimmable structure. Distinct from B2B drip/nurture sequences.

Write a short-form video script for TikTok, Instagram Reels, or YouTube Shorts — built on the hook→retention→payoff structure that drives watch-time. Use when asked to script a Reel, TikTok, Short, or any 15–60s vertical video. Produces a timed script with a 0–3s hook, retention beats with on-screen text and B-roll cues, a payoff, and a CTA — plus a caption and on-screen-text list. Distinct from long-form YouTube scripting.

Analyse a finished A/B test and write the readout — the result, whether it's statistically and practically significant, what it means, and the ship/no-ship call. Use when asked to analyse experiment results, write an A/B test readout, interpret test data, or decide whether to ship a variant. Produces a clear verdict with the lift and confidence, segment cuts, the risks (peeking, novelty, sample), and a recommendation. Distinct from planning a test — this reads results.

Audit a dataset for the quality problems that silently break analysis — missingness, duplicates, outliers, type and range errors, consistency, and freshness — and produce a prioritised fix list. Use when asked to assess data quality, audit a dataset, check data before analysis, or explain why numbers look off. Produces a structured quality report across the standard dimensions, the specific issues found (with the checks to run), severity, and how to fix each.

Decompose a north-star metric into a driver tree — the inputs and sub-inputs that actually move it — so a team knows which levers to pull. Use when asked to build a metric tree, break down a north-star metric, map metric drivers, or find the inputs behind an output metric. Produces a hierarchical tree from the top metric down to actionable input metrics, with the relationships, the highest-leverage levers, and what to instrument.

Draft SMART IEP goals, accommodations, and present-levels statements that are measurable and compliant in spirit. Use when asked to write an IEP goal, draft special-education goals, list accommodations, or write a present-levels (PLAAFP) statement. Produces measurable annual goals with baselines, criteria, and measurement methods, plus matched accommodations. A drafting aid for educators — not legal advice; the IEP team and local requirements govern.

Build a complete, standards-aligned lesson plan with clear objectives, a timed activity sequence, differentiation, and assessment. Use when asked to write a lesson plan, plan a class or lesson, design a teaching session, or structure instruction for a topic. Produces a ready-to-teach plan with measurable objectives, a minute-by-minute flow, materials, checks for understanding, and differentiation for varied learners.

Turn a skill's recommendations into real, executed actions — open the tickets, file the issues, post the updates — safely: dry-run preview, risk-classified, approval-gated, then recorded back to the brain. Use when asked to act on a plan, file tickets from a checklist, create issues from a PRD, execute the recommended next steps, or wire a skill's output into GitHub/Linear/Slack. Produces a dry-run actions plan with per-action risk, executes only after approval via the connected action MCP, and logs what was done. Nothing acts silently.

Maintain a durable, local markdown memory ('brain') of your product context, decisions, hypotheses, and stakeholders that other skills read from and write back to. Use when asked to set up a brain, ingest notes/artifacts into memory, recall what's known about a topic, log a decision with provenance, or run a weekly brain review. Produces a structured brain/ folder (knowledge, decisions, hypotheses, stakeholders, entities, source) with provenance-tagged facts, plus ingest/recall/record/review operations with approval-gated, append-only write-back.

Specify an autonomous or tool-using AI agent before building it. Use when asked to design an AI agent, define an agent's tools and guardrails, scope what an agent is allowed to do, or write an agent spec/PRD. Produces an agent spec — goal & scope, tools with permissions, the control loop, guardrails & approval gates, memory, escalation/handoff, evaluation, and failure handling.

Design an evaluation plan for an LLM or AI feature before shipping it. Use when asked how to evaluate a prompt/model/agent, set up an eval harness, define quality metrics for an AI feature, or build a regression gate. Produces an eval plan — task definition, datasets, metrics & rubrics, baselines, automated + human evals, a pass bar, and a regression gate.

Write a PRD for an AI-powered feature, covering the things normal PRDs miss. Use when asked to spec an AI/LLM feature, write a PRD for a feature that uses a model, or plan an AI capability (assistant, summarizer, generator, classifier). Produces an AI feature PRD — problem & UX of uncertainty, model approach, eval criteria, guardrails, fallback behaviour, the data flywheel, and cost/latency budget.

Document a dataset so others know what it is, how it was made, and when not to use it. Use when asked to write a datasheet for a dataset, document training/eval data, or assess whether a dataset is fit for a use. Produces a datasheet — motivation, composition, collection process, preprocessing, recommended uses & limits, distribution, and maintenance.

Model the cost and latency of an LLM feature before it ships and surprises the bill. Use when asked to estimate LLM API costs, set a latency/token budget, decide which model tier to use, or bring down the cost of an AI feature. Produces a cost & latency budget — token math per request, monthly cost projection, model tiering, caching/streaming levers, p95 latency targets, and a guardrail/alert plan.

Document a deployed ML/AI model so others can use it responsibly. Use when asked to write a model card, document a model's intended use and limitations, or prepare an AI model for review/launch. Produces a complete model card — intended use, training data, evaluation metrics across slices, limitations, ethical considerations, and a deployment checklist.

Design a Retrieval-Augmented Generation system end to end. Use when asked to design a RAG pipeline, a 'chat with your docs' feature, a knowledge assistant, or to debug why a RAG system gives wrong/ungrounded answers. Produces a RAG design doc — ingestion & chunking, embeddings & index, retrieval & reranking, the generation prompt, grounding/citations, evaluation, and failure modes with mitigations.

Write a board pre-read that's sent before the meeting so the meeting is about decisions, not status. Use when asked to prepare a board pre-read, a board update/package, or pre-meeting materials for a board. Produces a board pre-read — a TL;DR, the metrics dashboard vs. plan, what's working / what's not, the decisions and asks for the board, and risks — designed to be read in advance.

Allocate a finite budget or headcount across competing initiatives by return and strategic fit. Use when asked to allocate budget, decide where to invest, build a funding/portfolio plan, or make trade-offs across initiatives under a cap. Produces a capital-allocation plan — initiatives scored by expected return × strategic fit per dollar, a funded/unfunded split against the cap, the cut line, and the reasoning.

Write a crisp decision memo that drives a clear decision, not a discussion. Use when asked to write a decision memo, a recommendation memo, a one/six-pager for a decision, or to get leadership to decide something. Produces a decision memo — the decision & recommendation up front, the context, options with trade-offs, what you'd need to believe, risks, and the explicit ask with a deadline.

Write a strategy memo that commits to a bet and says what you won't do. Use when asked to write a strategy memo, articulate a strategy, make the case for a strategic direction, or align the team on where to focus. Produces a strategy memo — the strategic question, the diagnosis, the bet/approach, why now, explicit non-goals (what we're NOT doing), how we'll know it's working, and the risks.

Keep a running brag document of your accomplishments so reviews and promo cases write themselves. Use when asked to start or update a brag doc, log a win, track accomplishments, or prep evidence for a review/promotion. Produces a structured, dated accomplishment log — impact-first entries with metrics, scope, and the evidence link — grouped so it drops straight into a self-review or promo packet.

Map where you are against the next level and build a concrete plan to close the gap. Use when asked to map a career ladder, find the gap to the next level, build a development/growth plan, or figure out what to work on to get promoted. Produces a level-gap map — current vs. target competencies side by side, the specific gaps, and a prioritised 1–2 quarter plan of evidence-generating projects to close them.

Prepare for a 1:1 so it drives outcomes instead of becoming a status update. Use when asked to prep for a one-on-one, build a 1:1 agenda, prepare to talk to your manager (or a report), or raise something hard in a 1:1. Produces a focused 1:1 agenda — your top topics with the outcome you want for each, the asks, updates kept brief, and growth/feedback threads, tuned to direction (with your manager vs. with a report).

Build a promotion case that proves you're already operating at the next level. Use when asked to write a promo packet/case, prepare for a promotion committee, or make the case for a level-up or title change. Produces a promotion packet — the level-up thesis, evidence mapped to each next-level competency, scope/impact highlights, peer-quote slots, and the gaps to close before submitting.

Plan a compensation negotiation grounded in numbers and leverage, not nerves. Use when asked to negotiate salary, evaluate or counter a job offer, prepare for a comp conversation, or compare offers. Produces a negotiation plan — total-comp comparison across offers, your target/walk-away and BATNA, the value-based justification, the counter scripts, and what to negotiate beyond base.

Write a performance self-review that's specific, evidenced, and balanced. Use when asked to write a self-review, self-assessment, or self-evaluation for a performance cycle. Produces a complete self-review — accomplishments mapped to impact and competencies, growth areas owned honestly, and a forward-looking development plan, in the voice of the person being reviewed.

Build a data retention and deletion schedule grounded in legal basis. Use when asked to create a data retention policy, set retention periods, plan data deletion/minimisation, or answer 'how long can we keep this data?'. Produces a retention schedule — data categories with their retention period, legal/business basis, deletion trigger and method, plus flags for data kept with no basis or no defined period.

Assess GDPR compliance and build the core records (ROPA, lawful basis, DSAR, DPIA triggers). Use when asked to get GDPR-compliant, build a Record of Processing Activities, decide a lawful basis, handle data-subject requests, or check whether a DPIA is needed. Produces a GDPR assessment — a ROPA, lawful-basis mapping per activity, DSAR workflow, DPIA-trigger screen, and a prioritised gap list.

Map HIPAA Security Rule safeguards and run a risk analysis for systems handling PHI. Use when asked to become HIPAA-compliant, assess HIPAA safeguards, prepare for handling PHI/ePHI, or scope a BAA. Produces a HIPAA assessment — the administrative/physical/technical safeguards with required-vs-addressable status, a risk analysis, BAA scope, and a prioritised remediation plan.

Scope an ISO 27001 ISMS and build the Statement of Applicability across Annex A controls. Use when asked to implement ISO 27001, scope an ISMS, build a Statement of Applicability (SoA), or prepare for ISO 27001 certification. Produces an ISMS plan — scope & context, risk-treatment approach, an Annex A control applicability table (the SoA), and a prioritised implementation roadmap.

Assess SOC 2 readiness across the Trust Services Criteria and produce a gap remediation plan. Use when asked to prepare for a SOC 2 audit, run a SOC 2 readiness/gap assessment, scope controls, or get audit-ready. Produces a readiness report — scope & criteria, a control-by-control status, a weighted readiness score, prioritised gaps with owners, and the evidence each control needs.

Run a third-party / vendor security review and assign a risk tier with required controls. Use when asked to assess a vendor's security, run a third-party risk assessment, complete a security questionnaire about a vendor, or decide what due diligence a new tool needs. Produces a vendor risk assessment — a data/access-driven risk tier, the questionnaire focus, required evidence (SOC 2, pen test, DPA), residual risk, and an approve/conditional/reject recommendation.

Launch an autonomous THINK→EXECUTE→REFLECT experiment loop on a GPU project

Search papers from top AI/ML conferences

Daily arXiv paper recommendations with automatic deduplication

Check status of running autonomous experiment loops

Check GPU status, running experiments, and available resources

Refresh Obsidian dashboard and daily notes from current experiment state

Deep analysis of a single paper with figure extraction from arXiv source

Generate structured research progress reports

Run the AI Search Hub browser automation scripts for Yuanbao, LongCat, Doubao, Qwen, Gemini, Grok, and MiniMax. Use this skill when the user wants to ask one of those sites a prompt, auto-start or attach to a Chrome DevTools session on port 9222, seed an isolated debug browser profile from the user's local browser data, detect whether login is required, wait for the user to finish logging in if needed, and then continue automatically.

Creates a new CLI command following the Commander.js pattern in src/commands/. Handles command registration in src/cli.ts, telemetry tracking via tracked() wrapper, and option parsing. Use when user says add command, new CLI command, create subcommand, or adds files to src/commands/. Do NOT use for modifying existing commands or fixing bugs in existing commands.

Writes Vitest tests following project patterns: __tests__/ directories, vi.mock() for module mocking with vi.hoisted() for test-time factories, global LLM mock from src/test/setup.ts, environment variable save/restore in beforeEach/afterEach, vi.clearAllMocks() lifecycle, and test file organization. Use when user says 'write tests', 'add test coverage', 'test this', creates *.test.ts files, or when test failures appear in CI. Do NOT use for non-test code or for debugging without writing tests.

Discovers and installs community skills from the public registry. Use when the user mentions a technology, framework, or task that could benefit from specialized skills not yet installed, asks 'how do I do X', 'find a skill for X', or starts work in a new technology area. Proactively suggest when the user's task involves tools or frameworks without existing skills.

Adds a new LLM provider implementing LLMProvider interface with call() and stream() methods. Integrates with provider factory in src/llm/index.ts, config detection in src/llm/config.ts, and error handling via tracking and recovery. Use when adding a new model backend, integrating a third-party LLM API, or extending LLM platform support. Do NOT use for fixing bugs in existing providers, modifying existing provider behavior, or changing the LLMProvider interface.

Saves user instructions as persistent learnings for future sessions. Use when the user says 'remember this', 'always do X', 'from now on', 'never do Y', or gives any instruction they want persisted across sessions. Proactively suggest when the user states a preference, convention, or rule they clearly want followed in the future.

Add a new deterministic scoring check in src/scoring/checks/ that evaluates config quality. Follows the Check[] return pattern, uses point constants from src/scoring/constants.ts, and integrates via filterChecksForTarget() in src/scoring/index.ts. Use when user says 'add scoring check', 'new check', 'modify scoring criteria', or works in src/scoring/checks/. Do NOT use for display changes or refactoring scoring logic.

Sets up Caliber for automatic AI agent context sync. Installs pre-commit hooks so CLAUDE.md, Cursor rules, and Copilot instructions update automatically on every commit. Use when Caliber hooks are not yet installed or when the user asks about keeping agent configs in sync.

Add a new platform writer module in src/writers/ that generates and writes agent config files for a supported platform. Each writer exports a function that accepts a config interface, creates directories (rules/, skills/, mcp configs), writes files with proper formatting and frontmatter, and returns string[] of written file paths. Use when adding platform support for a new agent, integrating a new code AI tool, or extending caliber to support new targets. Do NOT use for modifying existing writers, refactoring scoring logic, or changing how writers are invoked.

Create ad-ready product images (single or collage) by back-solving sub-image sizes from target output ratio, grounding scene design with media_comprehension, generating images via image_generator with strict request params and actor-count control, and pairing each deliverable with a short social tagline for 小红书/抖音.

Create ad-ready product video from product images, with or without character/subject images. The workflow leverages AI-powered image composition, scene understanding, and video generation. Video prompts should follow commercial shot language—visual hooks, product presence, hero shots, detail showcase, function expression, and dynamic visuals.

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

A professional skill for App Evaluation (evaluating app's performance with score) and App Improvement (giving professional suggestions for improving the app's performance).

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Search and summarize the latest 7 days of AI news and X discussions using public sources plus browser-based X collection. Use for recent AI news, trends, X discussions, industry briefs, and summaries organized into hot topics, viewpoints, and opportunity areas.

An intelligent assistant specialized in handling media files (images/audio/video). **Only for media file analysis**, does not handle document types.\n\n✅ Media files that can be processed:\n- Images: .jpg, .jpeg, .png, .gif, .bmp, .webp, .svg\n- Audio: .mp3, .wav, .m4a, .flac, .aac, .ogg\n- Video: .mp4, .avi, .mov, .mkv, .webm, .flv\n\n❌ Files that cannot be processed (please do not trigger this skill):\n- Documents: .pdf, .doc, .docx, .txt, .md, .rtf\n- Spreadsheets: .xlsx, .xls, .csv, .tsv\n- Presentations: .pptx, .ppt, .key\n- Code: .py, .js, .ts, .java, .cpp, .go, .rs\n- Archives: .zip, .tar, .gz, .rar, .7z\n- Executables: .exe, .bin, .app, .dmg\n- Databases: .db, .sqlite, .sql\n- Configuration files: .json, .xml, .yaml, .yml, .toml, .ini\n- Web pages: .html, .htm, .css\n\n**Trigger conditions**: When the user explicitly requests to analyze image/audio/video content, or when the file extension belongs to the aforementioned media types.".

Analyzes and automatically optimizes existing agents by improving system prompts and tool configuration.

Creates new agents from user requirements by generating Python implementation and mcp_config.

Single-file TikTok/Douyin video download and traffic metrics via TikHub API using only httpx; optional persisted raw API JSON plus a stdlib post-processor emitting CSV and simplified JSON. Supports one URL or concurrent batch (max 10 workers). No dependency on any project codebase.

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Lightweight TikHub Xiaohongshu image-search workflow. Prioritizes single-request usage with curl or minimal Python, saves raw API JSON by default, and includes a small stdlib post-processor for CSV and simplified JSON. Use when the user wants Xiaohongshu keyword image search, page-based pagination, or structured note/image metadata from TikHub without a heavy wrapper.

Lightweight TikHub YouTube search and video-detail workflow. Prioritizes single-request usage with curl or minimal Python, saves raw API JSON by default, and includes a small stdlib post-processor for CSV and simplified JSON. Use when the user wants YouTube comprehensive search results, continuation-token pagination, or structured video metadata from TikHub without a heavy wrapper.

This skill is used for segmented reading and organization when facing large-scale knowledge bases or web pages. It captures original content segment by segment, summarizes key points in real-time, and continuously deposits them into the knowledge base, ensuring orderly information ingestion, clear structure, and traceability.

HTML 转图片 skill - 将 HTML 文件或内容通过 agent-browser 渲染并截图为图片。适用于生成信息图、社交媒体配图、数据可视化截图等场景。

X (Twitter) 抓取 skill - 通过 agent-browser (CDP) 抓取指定用户推文或首页推荐流，支持关键词过滤、Tab 切换、多格式输出。使用场景：按用户/关键词抓取时间线、查看首页推荐流、生成 RSS/JSON/Markdown。

小红书发布 skill - 通过 agent-browser (CDP) 自动发布小红书图文笔记，支持多图上传、标题正文填写、一键发布。使用场景：自动化发布图文笔记到小红书创作中心。

小红书搜索抓取 skill - 通过 agent-browser (CDP) 抓取小红书搜索结果，支持列表+详情、多格式输出。使用场景：按关键词抓取笔记列表与正文、生成 RSS/JSON/Markdown。

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Architecture specialist for software/system design, module and service boundaries, tradeoff analysis, and stakeholder synthesis. Uses context-aware methods such as diagnostic routing, design-twice comparison, ATAM-style risk analysis, CBAM-style prioritization, and ADR-style decision records.

Backend specialist for APIs, databases, authentication with clean architecture (Repository/Service/Router pattern). Use for API, endpoint, REST, database, server, migration, and auth work.

Design-first ideation that explores user intent, constraints, and approaches before any planning or implementation. Use for brainstorming, ideation, exploring concepts, and evaluating approaches.

Guide for coordinating PM, Frontend, Backend, Mobile, and QA agents on complex projects via CLI. Use for manual step-by-step coordination and workflow guidance.

Database specialist for SQL, NoSQL, and vector database modeling, schema design, normalization, indexing, transactions, integrity, concurrency control, backup, capacity planning, data standards, anti-pattern review, and compliance-aware database design. Use for database, schema, ERD, table design, document model, vector index design, RAG retrieval architecture, migration, query tuning, glossary, capacity estimation, backup strategy, database anti-pattern remediation work, and ISO 27001, ISO 27002, or ISO 22301-aware database recommendations.

Bug diagnosis and fixing specialist - analyzes errors, identifies root causes, provides fixes, and writes regression tests. Use for bug, debug, error, crash, traceback, exception, and regression work.

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Use when setting up or optimizing developer workflows in a monorepo, managing mise tasks, git hooks, CI/CD pipelines, database migrations, or release automation. Invoke for development environment setup, build automation, testing workflows, and release coordination.

Verify documentation references against the current codebase and propose updates for diff-affected docs. Use to check if docs still match reality (broken file paths, CLI commands, config keys, env vars, scripts) and to surface docs that may need updating after code changes.

Frontend specialist for React, Next.js, TypeScript with FSD-lite architecture, shadcn/ui, and design system alignment. Use for UI, component, page, layout, CSS, Tailwind, and shadcn work.

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