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Found 856 Skills
Objective task quality evaluation framework using quantitative KPIs. KPIs are automatically calculated by a hook when task files are modified and saved to TASK-XXX--kpi.json. Use when: reading KPI data for task evaluation, understanding quality metrics, deciding whether to iterate or approve based on data.
Consolidates objective metrics of a sprint. Use when you need quantitative data about deliveries, blockers, deviations, and velocity to feed retro, sprint review, or capacity decisions.
Measure and optimize growth using the AARRR (Pirate Metrics) framework with stage-specific KPIs and funnel analysis
Grafana Tempo distributed tracing backend. Covers TraceQL query language (span selectors, attribute scopes, pipeline operators, structural operators, metrics functions), trace ingestion via OTLP/Jaeger/Zipkin, Tempo architecture (distributor/ingester/compactor/querier/metrics-generator), full configuration reference with YAML, metrics-from-traces (span metrics, service graphs, TraceQL metrics), deployment modes (monolithic/microservices/Helm/Kubernetes), multi-tenancy, performance tuning, caching, and HTTP API. Use when working with distributed traces, writing TraceQL queries, deploying Tempo, configuring trace pipelines, or setting up Grafana-Tempo integrations (traces-to-logs, traces-to-metrics, traces-to-profiles).
X (Twitter) data platform skill — tweet search, user lookup, follower extraction, engagement metrics, giveaway draws, monitoring, webhooks, 19 extraction tools, MCP server.
A methodology for iteratively improving agent-facing text instructions (skills / slash commands / task prompts / CLAUDE.md sections / code-generation prompts) by having a bias-free executor actually run them and evaluating two-sidedly (executor self-report + instruction-side metrics). Keep iterating until improvements plateau. Use it right after creating or substantially revising a prompt or skill, or when you want to attribute an agent's unexpected behavior to ambiguity on the instruction side.
Research Facebook pages, public follower or following surfaces, and public posts using hosted collection capability. Use this when the user wants Facebook account research, follower-surface sampling, or public post metrics.
Query GA4 reports (users, sessions, conversions, funnels, realtime), manage properties / data streams / key events / custom dimensions / audiences / access bindings, and send Measurement Protocol events via the `ga4` CLI. Use this skill whenever the user mentions GA4, Google Analytics, property IDs starting with `properties/`, tracking events, engagement or traffic metrics, attribution, conversions, key events, audiences, BigQuery links, access roles, or realtime users — even if they don't explicitly say "GA4". Do not use for Google Search Console (see google-search-console skill) or generic web analytics where the source isn't GA4 (ask first).
Design hypothesis-driven ML/AI experiments before running them. Use this skill whenever the user wants to plan experiments, ablations, baselines, metrics, controls, seeds, logging, stop conditions, reviewer-proof evidence, or an experiment matrix for a paper claim before using run-experiment or writing results.
Aggregate and display system metrics with anomaly detection for a time period
Show federation health — peers, sessions, trust levels, and message metrics
Expert product specification and documentation writer. Use when creating PRDs, user stories, acceptance criteria, technical specifications, API documentation, edge case analysis, design handoff docs, feature flag plans, or success metrics. Covers the full spectrum from high-level requirements to implementation-ready specifications.