ReddRadar
Topic: claude
14,433 skills in this topic.
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prd-v04-persona-definition
Synthesize behavioral personas from prior stage evidence for journey mapping and marketing during PRD v0.4 User Journeys. Triggers on requests to define personas, create user profiles, identify target users, or when user asks "who are our users?", "define personas", "user profiles", "target users", "persona creation", "who uses this product?". Consumes CFD- (v0.1-v0.3), BR- (targeting from v0.3 Moat), FEA- (v0.3 Feature Value Planning). Outputs PER- entries with behavioral profiles and feature relationships. Feeds v0.4 User Journey Mapping.
mattgierhart/PRD-driven-context-engineering 26
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prd-v05-risk-discovery-interview
Surface risks through guided questioning, helping users consider pivots, constraints, and prioritization during PRD v0.5 Red Team Review. Triggers on requests to identify risks, stress-test the idea, perform red team review, or when user asks "what could go wrong?", "identify risks", "red team", "risk assessment", "challenge assumptions", "stress test the idea". Consumes all prior IDs (CFD-, BR-, FEA-, PER-, UJ-, SCR-) as interview context. Outputs RISK- entries with owner decisions and mitigations. Feeds v0.5 Technical Stack Selection.
mattgierhart/PRD-driven-context-engineering 26
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prd-v06-technical-specification
Define implementation contracts (APIs and data models) that developers will build against during PRD v0.6 Architecture. Triggers on requests to define APIs, design database schema, create data models, or when user asks "define APIs", "data model", "database schema", "API contracts", "technical spec", "endpoint design", "schema design". Consumes ARC- (architecture), TECH- (Build items), UJ- (flows), SCR- (screens). Outputs API- entries for endpoints and DBT- entries for data models. Feeds v0.7 Build Execution.
mattgierhart/PRD-driven-context-engineering 26
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prd-v08-release-planning
Define release criteria, deployment environments, and rollback strategies during PRD v0.8 Deployment & Ops. Triggers on requests to plan releases, define deployment criteria, or when user asks "how do we deploy?", "release criteria", "deployment plan", "rollback strategy", "go-live checklist". Outputs DEP- entries with deployment steps and release criteria.
mattgierhart/PRD-driven-context-engineering 26
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prd-v08-runbook-creation
Create operational playbooks for incident response, deployments, and maintenance during PRD v0.8 Deployment & Ops. Triggers on requests to create runbooks, document procedures, or when user asks "how do we handle incidents?", "runbook", "operational procedures", "on-call guide", "incident response", "maintenance procedures". Outputs RUN- entries with step-by-step operational procedures.
mattgierhart/PRD-driven-context-engineering 26
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prd-v05-technical-stack-selection
Make technology decisions for every product capability by discovering existing assets, evaluating vendor-aligned options, and categorizing as Reuse/Extend/Build/Buy/Integrate/Research during PRD v0.5 Red Team Review. Handles both greenfield and brownfield contexts. Triggers on "tech stack", "build or buy?", "what technologies?", "technical decisions", "what do we reuse?", "existing stack", "vendor constraint", "IBM-first", "what tools do we need?", "evaluate solutions", "select tech stack". Consumes FEA- (features), SCR- (screens), RISK- (constraints). Outputs TECH- entries with decisions, rationale, and cross-references. Feeds v0.6 Architecture Design.
mattgierhart/PRD-driven-context-engineering 26
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single-cell-rna-qc
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.
biocontext-ai/skill-to-mcp 21
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help
Provides information about using the skill-to-mcp server and how to install additional skills
biocontext-ai/skill-to-mcp 21
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jta
Translate JSON i18n files to multiple languages with AI-powered quality optimization. Use when user mentions translating JSON, i18n files, internationalization, locale files, or needs to convert language files to other languages.
ckanner/agent-skills 21
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prompt-optimizer
This skill should be used when users request help optimizing, improving, or refining their prompts or instructions for AI models. Use this skill when users provide vague, unclear, or poorly structured prompts and need assistance transforming them into clear, effective, and well-structured instructions that AI models can better understand and execute. This skill applies comprehensive prompt engineering best practices to enhance prompt quality, clarity, and effectiveness.
ckanner/agent-skills 21
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loom-crossplane
cosmix/loom 36
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loom-debugging
cosmix/loom 36
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loom-e2e-testing
cosmix/loom 36
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loom-event-driven
Event-driven architecture patterns including message queues, pub/sub, event sourcing, CQRS, and sagas. Use when implementing async messaging, distributed transactions, event stores, command query separation, domain events, integration events, data streaming, choreography, orchestration, or integrating with RabbitMQ, Kafka, Apache Pulsar, AWS SQS, AWS SNS, NATS, event buses, or message brokers.
cosmix/loom 36
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loom-grafana
Observability visualization with Grafana and LGTM stack. Dashboard design, panel configuration, alerting, variables/templating, and data sources.
USE WHEN: Creating Grafana dashboards, configuring panels and visualizations, writing LogQL/TraceQL queries, setting up Grafana data sources, configuring dashboard variables and templates, building Grafana alerts.
DO NOT USE: For writing PromQL queries (use /loom-prometheus), for alerting rule strategy (use /loom-prometheus), for general observability architecture (use senior-software-engineer with infrastructure focus).
TRIGGERS: grafana, dashboard, panel, visualization, logql, traceql, loki, tempo, mimir, data source, annotation, variable, template, row, stat, graph, table, heatmap, gauge, bar chart, pie chart, time series, logs panel, traces panel, LGTM stack.
cosmix/loom 36
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loom-prometheus
Prometheus monitoring and alerting for cloud-native observability.
USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery.
DO NOT USE: For building dashboards (use /loom-grafana), for log analysis (use /loom-logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus).
TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
cosmix/loom 36
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loom-python
cosmix/loom 36
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loom-security-audit
cosmix/loom 36
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loom-security-scan
cosmix/loom 36
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loom-sql-optimization
cosmix/loom 36
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loom-webhooks
cosmix/loom 36
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loom-accessibility
cosmix/loom 36
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loom-api-design
cosmix/loom 36
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loom-api-documentation
cosmix/loom 36