Skills directory · page 58

Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.

Models databases and writes type-safe queries with Prisma ORM. Use for modern Node.js/TypeScript database access.

Prisma ORM patterns for TypeScript backends — schema design, query optimization, transactions, pagination, and critical traps like updateMany returning count not records, $transaction timeouts, migrate dev resetting the DB, @updatedAt skipped on bulk writes, and serverless connection exhaustion. Use when writing a Prisma schema or query, or debugging transactions, migrations, or serverless connection limits.

Draft a detailed privacy policy covering data types, jurisdiction, GDPR and compliance considerations, and clauses needing legal review. Use when creating a privacy policy, updating data protection documentation, or preparing for compliance.

Publishes and maintains a problem brief: a page of findings, open decisions and questions for the operator, each with the problem, evidence and a recommended way out, kept as JSON that records every ruling so nothing is asked twice. Use by default, without being asked, whenever work turns up something the operator must decide (a finding with more than one way out, a risk, an open question, a choice between options), even mid-task and even when the operator only asked for an investigation. Also use when asked to build, publish, refresh or update a brief, findings report, open-questions or decisions page; when the operator answers, rules on or comments on anything a brief holds, in chat or in a comment on the page; when questions would otherwise go out through AskUserQuestion; and when retiring a brief whose work is done. Not for a progress, status or completion report with nothing to decide, for running a chorus review, or for converting chorus records to the shared schema.

Use when documenting an end-to-end business process (procurement, onboarding, handoffs) and finding where work waits. Maps it with process_documenter.py, measures stages with cycle_time_analyzer.py and finds bottlenecks with bottleneck_detector.py.

Use when the user asks to process / triage / address / handle PR reviews from CodeRabbit, SonarQube, Codex, and CI all together (CodeRabbit and Sonar only when they ran on the PR). First waits (polling every 1 min, max 30 min) until CodeRabbit, Sonar, and every CI check on the PR are in a terminal state — while a Codex review runs concurrently against the local diff. Then fetches unresolved threads from all three code-review sources plus failed CI checks, validates each against the actual code / log, handles invalid ones in place (reply on thread / NOSONAR comment), and presents a unified plan for fixing the valid ones (split into logical groups if more than 3). Invoked from la:pr-review, it returns the triaged list instead.

Honest-completion ruleset for changes that touch tests or the code they cover. Use before deleting, skipping, renaming, or rewriting a test, before weakening an assertion, and before hardcoding or stubbing an implementation to make a test pass. Also covers what to do when a test looks genuinely wrong.

Cut spend on software and suppliers: SaaS audit, category spend review, slow purchasing cycles, supplier consolidation. Use whenever the user asks which tools or vendors to cut, where money goes, or why buying takes so long.

Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.

Translate PRD intent, roadmap asks, or product discussions into an implementation-ready capability plan that exposes constraints, invariants, interfaces, and unresolved decisions before multi-service work starts. Use when the user needs an ECC-native PRD-to-SRS lane instead of vague planning prose.

Translate PRD intent, roadmap requirements, or product discussions into implementable solution plans, exposing constraints, invariants, interfaces, and unresolved decisions before starting multi-service work. Use when users need an ECC-native PRD-to-SRS channel rather than vague planning text.

Translate PRD intent, roadmap asks, or product discussions into an implementation-ready capability plan that exposes constraints, invariants, interfaces, and unresolved decisions before multi-service work starts. Use when the user needs an ECC-native PRD-to-SRS lane instead of vague planning prose.

Chinese-language product decision Agent. For mainland China internet product, operations, growth, monetization, data, project advancement, and organizational collaboration scenarios: product planning, requirements analysis, PRD, requirement prioritization, scheduling, version planning, Roadmap, MVP, canary release, launch, iteration, growth stagnation, user acquisition, ad placement, channels, viral referral, CAC, LTV, ROI, retention, conversion, DAU/MAU, GMV, funnel, community operations, content supply, creators, user operations, campaign operations, private domain, membership, pricing, metric anomalies, data definitions, event tracking, A/B Test, user feedback, customer service/sales feedback, competitive pressure, insufficient resources, project delays, requirement churn, boss adding ad-hoc requirements, cross-department collaboration, team conflict, OKR/KPI, goal breakdown, retrospectives, etc. When triggered, act like a senior internet product lead: first determine the real problem, current stage, core blocker, key constraints, stakeholders, and sufficiency of evidence, then give the next step most worth executing. Answer in Chinese by default; do not lecture on theory, quote source text, explain history, or reveal the backend method source.

Validate product ideas: map assumptions, plan discovery sprints, test problem-solution fit. Use whenever the user asks if an idea is worth building.

Validate the why before building through four product diagnostics — a YC-style product diagnostic that produces PRODUCT-BRIEF.md with a go/no-go recommendation, a founder review scoring product-market-fit signals, a user journey audit measuring time-to-value, and ICE feature prioritization. Use when pressure-testing product direction, choosing between features, sanity-checking a launch, or converting a vague idea into a product brief.

Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.

PM toolkit: RICE prioritization, customer interview synthesis, PRDs and go-to-market. Use whenever the user asks what to build next, to rank features, write a PRD or sum up interview notes.

Brainstorm 5 unique, memorable product names with rationale aligned to brand values and target audience. Use when naming a new product, rebranding, or exploring product name ideas.

Use when planning or synthesizing user research: choosing the method, deciding how many participants, or turning coded notes into insights. Runs study_designer.py, saturation_planner.py and insight_synthesizer.py, which refuses single-source insights.

Use when a product request needs routing across the product-team skills (prioritization, OKRs, UX research, experiments, discovery, roadmaps), or to run the continuous discovery loop. Routes with product_goal_router.py and gates with discovery_cadence_tracker.py and ost_linter.py.

Strategic product leadership toolkit for Head of Product including OKR cascade generation, market analysis, vision setting, and team scaling. Use for strategic planning, goal alignment, competitive analysis, and organizational design.

Head of Product: quarterly OKRs cascaded from company to team, product vision, roadmap, team structure. Use whenever the user asks to set OKRs, a vision or roadmap, or align teams on strategy.

Create a comprehensive product strategy using the 9-section Product Strategy Canvas — vision, segments, costs, value propositions, trade-offs, metrics, growth, capabilities, and defensibility. Use when building a product strategy, creating a strategic plan, or defining product direction.

Brainstorm an inspiring, achievable, and emotional product vision that motivates teams and aligns stakeholders. Use when defining or refining a product vision, creating a vision statement, or aligning the team around a shared direction.

Local-evidence production readiness audit for shipped apps, pre-launch reviews, post-merge checks, and "what breaks in prod?" questions without sending repo data to an external audit service. Use when auditing production readiness before launch, after a merge, or when asked what breaks in prod.

Build the standalone Forge artifact with strict routing inputs and confirm its static output exists.

Autonomously deep-scan entire codebase line-by-line, understand architecture and patterns, then systematically transform it to production-grade, corporate-level professional quality with optimizations

Codified expertise for production scheduling, job sequencing, line balancing, changeover optimization, and bottleneck resolution in discrete and batch manufacturing. Informed by production schedulers with 15+ years experience. Includes TOC/drum-buffer-rope, SMED, OEE analysis, disruption response frameworks, and ERP/MES interaction patterns. Use when scheduling production, resolving bottlenecks, optimizing changeovers, responding to disruptions, or balancing manufacturing lines.

Codified expertise for production scheduling, job sequencing, line balancing, changeover optimization, and bottleneck resolution in discrete and batch manufacturing. Based on the knowledge of production schedulers with 15+ years of experience. Includes theory of constraints/drum-buffer-rope, quick changeover, overall equipment effectiveness analysis, disruption response frameworks, and enterprise resource planning/manufacturing execution system interaction patterns. Use when scheduling production, resolving bottlenecks, optimizing changeovers, responding to disruptions, or balancing manufacturing lines.

Guide technical communication for software developers. Covers email structure, team messaging etiquette, meeting agendas, and adapting messages for technical vs non-technical audiences. Use when drafting professional messages, preparing meeting communications, or improving written communication.

When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," or "building many pages for SEO." For auditing existing SEO issues, see seo-audit.

Use when building many SEO pages from a template and data (location, integration, comparison or directory pages), before generating them. Designs URL patterns with url_pattern_generator.py and guards against thin-content penalties.

Build Progressive Web Apps (PWAs) with offline support, installability, and caching strategies. Trigger whenever the user mentions PWA, service workers, web app manifests, Workbox, 'add to home screen', or wants their web app to work offline, feel native, or be installable.

Build and maintain a three-layer project awareness system that gives Claude Code both the 30,000-foot architectural view AND the ability to drill into specifics — without exceeding context limits. Use this skill whenever: starting work on any project with 10+ source files; the user says "bootstrap", "set up awareness", "analyze this project", "build the map"; the user says "you're missing the big picture", "you don't understand the architecture", "you keep forgetting", "update the docs"; a CLAUDE.md exists with an [AWARENESS] section (this means the system is already bootstrapped — load and follow it); or when starting an Agent Teams session on any project (each agent must load its subsystem doc). This skill supersedes and works alongside deep-focus. Deep-focus is HOW you work carefully; project-awareness is HOW the project's knowledge is organized and maintained.

Operate execution flow across GitHub and Linear by triaging issues and pull requests, linking active work, and keeping GitHub public-facing while Linear remains the internal execution layer. Use when the user wants backlog control, PR triage, or GitHub-to-Linear coordination.

Coordinate execution flow between GitHub and Linear by triaging issues and pull requests, linking active work, and keeping GitHub externally visible while Linear serves as the internal execution layer. Use when the user needs backlog control, PR triage, or GitHub–Linear coordination.

Project-specific skill template covering architecture, patterns, testing, and deployment guidance.

Project-specific skill template covering architecture, patterns, testing, and deployment guidance.

Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.

Set up monitoring with Prometheus and Grafana: metrics, exporters, alerting rules, dashboards, and SLO tracking. Use for observability.

Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement. Use when the user runs /si:promote or asks to make a learned behavior permanent.

Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation) Use when: prompt caching, cache prompt, response cache, cag, cache augmented.

Optimize LLM cost and latency with prompt caching: cacheable prefixes, cache-control headers, context layout, and cache-aware prompting. Use for high-volume apps.

Optimize LLM prompt caching hit rate to reduce API costs and improve latency. Analyzes prompt structure, identifies cacheable vs non-cacheable content, and recommends restructuring to maximize cache reuse. TRIGGER when: user says "prompt cache", "cache hit rate", "reduce LLM cost", "optimize token usage", "cheaper LLM calls", or asks about prompt caching strategies for OpenAI/Anthropic/other providers. DO NOT TRIGGER when: user just wants to optimize a single prompt's quality (use prompt-optimizer instead), or asks about general caching infrastructure.

Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt design.

Use when a marketing team's AI prompts need testing, versioning or governance, before shipping a prompt. A/B tests prompts against cases with prompt_tester.py and keeps diffed versions with prompt_versioner.py.

Design effective prompts for LLMs: role framing, structured output, chain-of-thought, few-shot, and evaluation. Use to get reliable model behavior.

Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming