Skills
97,725 packaged capabilities and playbooks for agents. Install any of them with one command.
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OpenTelemetry - vendor-neutral observability framework for distributed systems. Provides traces, metrics, and logs with standardized instrumentation and exporters. USE WHEN: user mentions "opentelemetry", "otel", "distributed tracing", "observability", asks about "how to trace microservices", "opentelemetry setup", "jaeger integration", "prometheus metrics" DO NOT USE FOR: Application logging only - use logging skills instead, APM vendor-specific - use vendor docs, Simple monitoring - Prometheus/Grafana may be sufficient
Formulate and implement operations research optimization models—LP, MIP/QP, constraint programming, network flows, assignment, VRP, scheduling, resource allocation, inventory/production planning; heuristics and metaheuristics; sensitivity and infeasibility diagnosis; solver integration (OR-Tools, Gurobi, CPLEX, HiGHS, PuLP, Pyomo); production OR APIs (timeouts, warm starts). Use for operations research, OR engineer, optimization model, linear programming, mixed integer programming, MIP, VRP, vehicle routing, scheduling optimization, OR-Tools, Gurobi, constraint programming, resource allocation optimization, infeasible model, metaheuristic—not ML prediction (data-scientist), SCM strategy without optimization math (supply-chain-manager), WMS features (wms-developer), simulation platforms (simulation-software-engineer), generic backend (senior-software-engineer), dbt/warehouse (analytics-data-engineer).
Main entry point for working with Opper (https://opper.ai), the AI gateway for agents. Use when the user mentions Opper without choosing a surface: "set up Opper", "try Opper", "build with Opper", "migrate to Opper", or "help me with Opper". Explore context and route to opper-mcp for agent-assisted setup, platform operations, and model tests; opper-cli for explicit CLI and shell workflows or launching coding agents through Opper; opper-api for application code (the OpenAI, Anthropic or Google SDKs and agent frameworks on the compat endpoints), raw HTTP, and platform concepts; or opper-multimodal for media, files, and realtime voice. Own setup, verification, and follow-up.
Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to customer opportunities, possible solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when the team is unclear what to build next, when multiple opportunities compete, or before writing a PRD for a complex feature space.
Kernel-level proxy protection via proxy-ns — forces ALL traffic (TCP/UDP/DNS) through Tor using Linux network namespaces. Unlike proxychains, this works with Go/Rust/static binaries, prevents DNS leaks, and is impossible for applications to bypass. Includes Tor circuit rotation, IPv6 leak prevention, stealth headers, and jitter configuration. Use AT THE START of any pentest or recon engagement — before any probes that could leak your source IP. Setup once at the beginning of a session and run the entire toolchain inside the proxy-ns shell
Coordinate an end-to-end Jira ticket workflow from ticket fetch through per-task implementation. Use this skill when the user provides a Jira URL, says "work on ticket PROJECT-123", "resume PROJECT-123", "continue this Jira ticket", "start the Jira workflow", or asks for status on a ticket without naming a specific phase. This top-level coordinator keeps SKILL.md as a routing layer, loads bundled references just in time, and dispatches execution-heavy work to downstream skills or co-located utility subagents.
Instrument applications with the OpenTelemetry SDK and prove the telemetry is good by validating it against a local Kopai backend. Use when setting up observability, adding tracing/logging/metrics, deciding what to instrument or which attributes to add, retrofitting OTel into an existing codebase, threading context through call chains, configuring sampling, or when traces/logs/metrics aren't appearing after setup. Also use when users say things like "my traces aren't showing up", "I don't see any data", or "how do I add observability to my app". Do NOT use to investigate existing telemetry for a root cause (use root-cause-analysis), to build dashboards (use create-dashboard), or to instrument LLM and agent calls (use otel-genai-instrumentation).
Keep every outreach reply warm until it turns into a yes. Finds the leads your cold outreach did not convert yet ('not now', 'happy to connect', 'send me something', went silent after replying) and nurtures them on a 6-week cadence: picks the right case study, playbook or article per lead from your own content library (Notion, Google Drive, a website section or a pasted list), writes the picks onto the lead as custom attributes, then duplicates and fills your nurture campaign in La Growth Machine so touches, likes and follow-ups run natively. More positive replies, every campaign compounds, new content re-activates matching leads, content gaps say what to produce next. Use for: nurture my not-now leads, follow up on vague replies, re-engage leads that went quiet, build a nurture cadence, match content to leads, 'relancer mes leads pas maintenant'. Works from the LGM MCP or any outreach tool's CSV. For SDRs, founders, agencies, Heads of Sales. Maintained by La Growth Machine
Transform an output-focused roadmap (feature list) into an outcome-focused one. Rewrites initiatives as outcome statements reflecting user and business impact. Use when a roadmap lists features instead of results, when making a roadmap more strategic, or when communicating what success looks like vs what will be built.
Analyze local Q&A session JSONL files and produce a complete, auditable English Markdown weekly report over consecutive time windows, with all data required for downstream Feishu document and whiteboard rendering. Use for requests such as "analyze the latest week of sessions," "generate a community Q&A weekly report," or "compare with last week." This skill does not ingest other message sources or create/upload online documents.
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
Run a cumulative daily or retrospective sweep of research papers on a chosen topic, audit their claims, methods, integrity signals, and independent support, then identify overlooked but feasible project or business opportunities in a detailed source-grounded report. Use when asked to monitor papers every day, mine buried research, evaluate whether a paper is credible or reproducible, find unimplemented research ideas, or separate promising work from hype, weak evidence, and retracted or contradicted results.
Divide-and-conquer implementation from specs/plans. Decomposes a reference document into independent tasks, assigns each to a builder agent, executes in parallel waves respecting dependencies, then integrates results. Use when you have a spec, PRD, plan, or large feature to implement quickly with parallel execution.
Design and audit partner co-marketing launches, integration announcements, joint messaging, launch assets, approval workflows, channel plans, attribution, lead routing, marketplace listings, webinars, case studies, incentives, enablement, partner commitments, and post-launch follow-up. Use when a product launch depends on a partner ecosystem or joint go-to-market motion.
Run a PDCA cycle, Plan Do Check Act improvement cycle, or structured improvement project. Guides through problem analysis, piloting, verification, and standardisation. Distinguished from 8D: PDCA is for proactive improvement initiatives, 8D is for reactive defect response. Use for process optimisation, lessons learned implementation, and quality objectives.
TRIGGER THIS when conducting performance reviews, writing manager feedback, creating self-assessments, building peer feedback, developing PIPs, creating development plans, or handling difficult performance conversations. Helps write constructive, specific, actionable feedback that develops performance and documents performance management appropriately.
Use this skill when you need to design JMeter test plans with Thread Groups, samplers, data sets, assertions, timers, CLI runs, and HTML reports; triggers include JMeter performance testing, performance testing, and performance-test-jmeter.
Generate AIAG-VDA compliant Process FMEAs with proper Severity/Occurrence/Detection ratings, RPN calculations, and countermeasure recommendations. Covers MNMUK departments (Machine Shop, Damper, LVA, FML). USE WHEN user says 'PFMEA', 'FMEA', 'failure mode', 'risk analysis', 'RPN', 'severity occurrence detection', or 'process risk assessment'. Integrates with AutomotiveManufacturing, ControlPlan, and A3criticalthinking skills.
Design comprehensive test cases using PICT (Pairwise Independent Combinatorial Testing) for any piece of requirements or code. Analyzes inputs, generates PICT models with parameters, values, and constraints for valid scenarios using pairwise testing. Outputs the PICT model, markdown table of test cases, and expected results.
Improve router-facing pipeline and reflection narration to reduce noisy status churn and make Step 0/Reflection outcomes explicit. Use when updating Router output contract, reflection reminder wording, or post-pipeline notification batching.
Use when handling BK-CI pipeline variables, such as variable lifecycle, runtime passing, cross-task updates, field extension, and conversion between YAML and internal models. Prefer it when the user wants to change the main variable path rather than ordinary pipeline steps.
Builds investor pitches and funding proposals that prove a 'secret' through data and narrative — answering 'Why Now?' and 'Why Us?' using Thiel's definite optimism framework. Use when creating pitch decks, internal presentations, or funding requests.
Guidance for developing under a projects managed by pixi. Always use when workspace managed by pixi (have pixi.toml or pixi.lock in root directory.) Covers all you should know while developing under a pixi-based project: pixi environment commands (install, run, shell, add, task), multi-environment management (-e flag, features), task configuration in pixi.toml, dependencies (conda vs PyPI), lock files, and development workflows. Helps with environment setup, package management, running tasks, debugging pixi.toml errors, and production deployment patterns.
Use when capturing an idea, drafting a design, or tracking work-in-progress in a repo's plans/ directory — creating or updating a plans/YYYY-MM-DD-topic.md file (including a bug, idea or risk turned up incidentally), asking what plans exist or what to work on next, here or across every repo, choosing or advancing a status, retiring a landed/abandoned plan once its content has a permanent home elsewhere, migrating a repo's legacy monolithic plan file (PLAN.md, DESIGN.md, ...) onto this convention, or auditing AGENTS.md/README.md/docs for planning/status/future-work content that has drifted in and belongs in plans/ instead. Also owns where a plan file may live and what may be written in it: a work, client or employer repo that cannot take a plans/ directory keeps its plans in the store outside every working tree ($PLANS_HOME), routed per repo by config; an idea with no repo yet is filed unscoped and graduated later; and no plan committed to a repo you publish may name a client, employer or internal project.
Write, check, repair and publish a plan page: a project's plans and subject files under its plans directory, rendered by .agents/pstack/plan-page.mjs and rendered as one local HTML page per subject with a local index of every subject, and published to claude.ai at each hand-back for comments and feedback. The page is how planned work hands back to the user. Use before writing or changing a plan, a subject file in <plans>/topics or its page; at every stop that hands back work with a plan, such as a review verdict other than a review-only panel's, a next answer or a playbook's close; before writing or updating a PR body, which renders from the PR's plan, or a comment about your commits on someone else's PR; when a plan page or its claude.ai artifact looks wrong or refuses to render; to republish a page; or to change the page shape or a playbook's page sections.
Build, review, debug, configure, migrate, or plan Playwright browser automation and E2E tests with current docs. Use for @playwright/test, playwright, playwright.config, locators, getByRole, locator.visible, frameLocator, assertions, fixtures, Page Object Model, storageState auth, test locks, retryStrategy, network mocking, HAR, traces, UI Mode, codegen, CI sharding, Docker, APIRequestContext, stories/galleries component testing, accessibility, screenshots, visual comparisons, AbortSignal, and Playwright MCP or CLI agent tooling.
Auto-update GTME portfolio when HubSpot deals close. Links deal outcomes (won/lost, revenue, cycle time) to the skills, automations, and outreach that influenced them — building VP BD transition evidence automatically. Runs daily at 7am CST or on-demand. Use when: 'portfolio update', 'deal closed', 'link deal to portfolio', 'gtme evidence', 'what did I influence', 'career evidence', 'transition tracker'.
Design positioning and messaging frameworks for your company using the Use Case Messaging Canvas and Opposites method. Use whenever you need to define your positioning, build a messaging framework, create a Use Case Canvas, or bridge the gap between ICP and copy. Triggers include 'position yourself,' 'messaging framework,' 'Use Case Canvas,' 'how should we position,' 'our messaging is all over the place,' 'we skip straight to copy,' 'Opposites method,' 'Old Way vs New Way,' 'positioning workshop,' 'value prop,' 'one-liner,' 'elevator pitch,' 'positioning line,' or any situation where you have an ICP but your messaging is missing or inconsistent. BOUNDARY: This skill designs POSITIONING and MESSAGING frameworks. For ICP building (the step BEFORE), see icp-builder. For writing actual LinkedIn copy, see a LinkedIn posting skill. For proposals, see a proposal generator skill.
PostgreSQL relational database. Covers SQL queries, indexes, constraints, and performance. Use when working with PostgreSQL. USE WHEN: user mentions "postgres", "postgresql", "pg_", asks about "JSONB queries", "window functions", "recursive CTE", "row level security", "full text search", "partitioning", "pgBouncer", "replication" DO NOT USE FOR: MySQL syntax - use `mysql` instead, MongoDB - use `mongodb` instead, Oracle PL/SQL - use `plsql` instead, SQL Server T-SQL - use `tsql` instead
Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.
Safe household actions, offline memory, and evidence-backed answers on top of the full Home Assistant control surface. Trigger phrases: `turn the apartment into movie-night mode`, `which windows are open`, `why did my automation fail`, `check my Home Assistant health`, `use Home Assistant`, `run Home Assistant`.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.