Processing
Data transformation and parsing
agent-best-practices
by langwatch
Expert AI engineering consultant for your agent development practices. Audits your codebase, traces, evaluations, and scenarios against best practices, then guides you to close the gaps, starting from low-hanging fruit and going deeper. Use when you want to level up your agent's engineering quality.
browser-test
by langwatch
"Validate a feature works by driving a real browser with Playwright MCP. No test files — just interactive verification."
test-locally
by open-metadata
Build and deploy a full local OpenMetadata stack with Docker to test your connector in the UI. Handles code generation, build optimization, health checks, and guided testing.
abuse-detection
by pollinations
Detect and analyze abusive accounts on Pollinations. IP clustering, multi-signal scoring, ban recommendations. Use when investigating abuse, bot farms, or suspicious usage patterns.
model-debugging
by pollinations
Debug and diagnose model errors in Pollinations services. Analyze logs, find error patterns, identify affected users.
code-formatting
by pollinations
Format code on the current branch using Biome. Use when asked to format, lint, or clean up code before committing or creating a PR.
react-effects
by coder
Guidelines for when to use (and avoid) useEffect in React components
analyzing-outlook-pst-for-email-forensics
by mukul975
Analyze Microsoft Outlook PST and OST files for email forensic evidence including message content, headers, attachments,
screenpipe-health
by screenpipe
Check Screenpipe health status, process state, and diagnose common issues
screenpipe-api
by screenpipe
Query the user's data via the local screenpipe REST API at localhost:3030 — screen recordings, audio, UI elements, usage analytics, meetings, connected services, and the user's persistent memory store. Use for questions about screen activity, meetings, apps, productivity, media export, retranscription, connections, OR to save / remember / store information for later (POST /memories — survives across sessions, queryable by external agents).
screenpipe-api
by screenpipe
Query the user's screen recordings, audio, UI elements, and usage analytics via the local Screenpipe REST API at localhost:3030. Use when the user asks about their screen activity, meetings, apps, productivity, media export, retranscription, or connected services.
scvi-tools
by anthropics
Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.
audit-flow
by zebbern
Interactive system flow tracing across CODE, API, AUTH, DATA, NETWORK layers with SQLite persistence and Mermaid export. Use for security audits, compliance documentation, flow tracing, feature ideation, brainstorming, debugging, architecture reviews, or incident post-mortems. Triggers on audit, trace flow, document flow, security review, debug flow, brainstorm, architecture review, post-mortem, incident review.
code-to-diagram
by zebbern
"Analyze codebases and automatically generate architecture diagrams, flowcharts, and org charts. Uses AST parsing to map import dependencies for Python, JS/TS, Go, and Java, outputting Mermaid or SVG files. Triggered when users ask to visualize code architecture, understand dependencies, draw a flowchart, or create a module diagram from source code."
route-to-openapi
by zebbern
"Generates RESTful API documentation (OpenAPI 3.0 / Swagger spec) by scanning route definitions in code for Flask, FastAPI, Express, Gin, and other frameworks. Trigger when users ask about API documentation, OpenAPI, Swagger, endpoint docs, generating docs from code, or extracting endpoints."
by zebbern
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
chart
by Kilo-Org
Use when the user asks to visualize data with charts, graphs, or plots using the chart tool (bar, line, scatter, pie, time series, etc.).
agent-improve
by langwatch
Turns production evidence into tested improvements for your AI agent. Forms hypotheses from real traces and analytics, explains the reasoning behind each one, then executes with the user: scenario tests that reproduce production failures, prompt and code changes as reviewable PRs, new evaluators and monitors that capture production signals, and experiments that settle open questions. Use when you want to know what to do next to improve your agent.
errors-api-e2e
by triggerdotdev
End-to-end smoke test for the public Errors HTTP API (error groups). Seeds failed runs into ClickHouse so the error materialized views populate, then drives the real endpoints against the running webapp — list (with filters + pagination), retrieve, resolve/ignore/unresolve, the filter[error] runs filter, user attribution via the trigger.dev mint-token -> JWT exchange, and the 401/403/404 negatives. Use for "smoke test the errors API", "test the errors API e2e", "prove the errors endpoints work", or to re-verify after changes.
intent-recognition
by n8n-io
Classifies automation requests using two decisions: anchor (which primitive owns the top-level control flow — workflow-anchored, agent-anchored, needs-clarification, or out-of-scope) and embeds_other (whether the other primitive appears embedded inside — an agent step inside a workflow, or a workflow invoked as an agent tool). Must be used whenever the current turn requires choosing or reconsidering the intent of an automation request, including compound requests, independent automations introduced mid-build, one-off questions or reports that need external systems you cannot query directly, and requests that need clarification before an anchor can be chosen. Do not load for routine edits or extensions when the conversation already targets a workflow or Agent.
n8n:loom-transcript
by n8n-io
Fetch and display the full transcript from a Loom video URL. Use when the user wants to get or read a Loom transcript.
data-table-manager
by n8n-io
Load before calling data-tables or parse-file. Use for natural standalone requests like "what data tables do I have?", "show/list my tables", or "what columns are in this table?", and whenever the user asks to list, show, create, inspect, import, seed, query, update, clean up, rename columns in, or delete data tables and rows, especially from CSV/XLSX/JSON attachments. Also load before building or planning workflows that create or write to Data Tables (then load workflow-builder before build-workflow).
planning
by n8n-io
ONLY for coordinated multi-artifact work: multiple workflows with dependencies, shared data-table schema/migration across tasks, or the user explicitly asked to review a plan first. Load create-tasks via load_tool before calling it (search "create tasks" if not visible). Do NOT use for new one-off workflows, single-workflow edits, verification-only requests, or standalone data-table ops — use workflow-builder or data-table-manager instead.
n8n:create-instance-ai-eval
by n8n-io
Authors a new Instance AI workflow eval case — written locally as JSON, calibrated against a real build, then pushed to the LangTracer suite CI runs — build cases, behaviour/process cases, credential cases, and seeded (mid-conversation) cases — with intent-driven expectations. Use when adding or changing an Instance AI workflow eval, or debugging why one is flaky.