Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Helps users migrate from Azure Cache for Redis (ACR/OSS) Basic, Standard, and Premium tiers to Azure Managed Redis (AMR). Provides SKU mapping, real-time pricing scripts, cache metrics assessment, automated migration via ARM REST APIs with DNS switching, and IaC template migration (ARM, Bicep, Terraform). Use when users ask about: Redis migration, ACR to AMR, OSS to AMR, automated migration, DNS switch migration, cache retirement deadline, ACR retirement date, SKU selection, AMR vs ACR features, feature compatibility, Redis module support, pricing comparison, cache upgrade, Basic/Standard/Premium tier migration, P1/P2/C3 cache migration, AMR SKU recommendation, migration rollback, migration validation, connection string changes, port changes, cache assessment and metrics, IaC template migration (ARM, Bicep, Terraform), or checking for amr-migration-skill updates. Do NOT use for: Enterprise (ACRE) tier migrations, creating new Redis caches, or general Redis performance tuning.
Core Python library for astronomy/astrophysics: units with dimensional analysis, celestial coordinate transforms (ICRS/Galactic/AltAz/FK5), FITS I/O, tables (FITS/HDF5/VOTable/CSV), cosmology (Planck18, distance/age), precise time (UTC/TAI/TT/TDB, Julian, barycentric), WCS pixel-world mapping, model fitting. For general tables use pandas/polars; for radio interferometry use CASA.
Define custom attributes, custom object types, and site preferences for B2C Commerce using metadata XML. Use this skill whenever the user needs to add a field to products, orders, or customers, create a new custom object type, set up site preferences, or extend the B2C data model. Also use when they ask about system-objecttype-extensions.xml, custom-objecttype-definitions.xml, attribute groups in Business Manager, or data model definitions — even if they just say "add a field to products" or "I need a new object type".
Use when the user needs HTML Canvas, SVG graphics, data visualization, generative art, or interactive visual elements with D3.js or similar libraries. Triggers: user says "canvas", "SVG", "chart", "data visualization", "D3", "generative art", "animation", "interactive graphics", drawing on screen.
Scan support tickets, Slack channels, NPS scores, and usage patterns to flag accounts showing early churn indicators. Produces a weekly risk scorecard with severity tiers, root cause hypotheses, and suggested save plays per account. Designed for seed/Series A teams where the founder or a single CSM manages all accounts manually.
Cowork-style sweep of a folder of receipts, statements, and expense exports -- categorizes every transaction, matches receipts to statement lines, flags policy violations and anomalies, and outputs a clean expense report plus a findings memo.
Use when querying or mutating Datex Studio storage components via the `$db` predicate DSL — function-tier-only Mongo-backed access to `*-storage.json` configurations. Covers the fluent predicate operators (`.equals`, `.ne`, `.gt`/`.gte`, `.lt`/`.lte`, `.in`, `.isNull`/`.isNotNull`, regex via `.includes`, composed with `.and`/`.or` inside `.where`), result-row TypeScript-optionality semantics, the implicit `id` column, the `required: true` read-then-patch trap, and schema-change audit checklist. Flow datasources that back grids or selectors over `$db` are covered in the flow-db-datasources reference. Triggers: "query the storage", "add/update/remove rows in xxx_storage", "write a $db predicate", "filter by storage column", "$db predicate with AND/OR/null", "$db query returning wrong rows", "patch validation error", "TypeScript accepted my predicate but it doesn't work at runtime". For authoring the calling function itself, see function-creator.
Run a structured validity audit on OKRs, KPIs, North Star Metrics, or any success-metric set. Produces a severity-rated issue list with concrete fixes — catches vanity metrics, unfalsifiable key results, outputs disguised as outcomes, gameable targets without guardrails, and metrics disconnected from business value. Use when reviewing OKRs, goals, KPIs, dashboards, or success metrics, or as a validation step after defining metrics in a spec, roadmap, or strategy doc.
Power BI REST API and Fabric REST API automation. PROACTIVELY activate for: (1) calling Power BI REST APIs, (2) embed-token generation (App Owns Data, User Owns Data), (3) service-principal authentication for Power BI, (4) dataset refresh API and refresh status polling, (5) push datasets and streaming, (6) Admin API (workspace/dataset enumeration), (7) Power BI Embedded and the JavaScript SDK (powerbi-client), (8) export-to-file API (PDF/PPTX/PNG), (9) Power BI automation via PowerShell (MicrosoftPowerBIMgmt), (10) Scanner API for tenant inventory, (11) app registration in Microsoft Entra ID. Provides: REST endpoint reference, OAuth/MSAL token recipes, embed-token patterns, refresh automation scripts, JavaScript SDK examples, and PowerShell module recipes.
Reviews sqlx database code for compile-time query checking, connection pool management, migration patterns, and PostgreSQL-specific usage. Use when reviewing Rust code that uses sqlx, database queries, connection pools, or migrations. Covers offline mode, type mapping, and transaction patterns.
TMDL (Tabular Model Definition Language) mastery for Power BI semantic models. PROACTIVELY activate for: (1) writing or editing TMDL files, (2) TMDL syntax (model.tmdl, database.tmdl, relationships.tmdl, table folders), (3) TMDL serialization (TmdlSerializer, folder-based vs single-file), (4) TMDL view in Power BI Desktop, (5) TMDL vs TMSL vs BIM format selection, (6) TMDL expressions, calculation groups, perspectives, cultures, translations, annotations, (7) TMDL roles and security, (8) TMDL ref keyword and createOrReplace scripts, (9) TMDL CI/CD integration (Git, deployment), (10) TMDL hierarchies and partitions. Provides: TMDL syntax reference, folder-layout templates, serialization patterns, ref/createOrReplace recipes, and Git integration setup.
LoRA, full fine-tuning, DPO preference tuning, VLM training, function-calling tuning, reasoning tuning, and BYOM uploads on Together AI. Reach for it whenever the user wants to adapt a model on custom data rather than only run inference, evaluate outputs, or host an existing model.
Inspect existing alerts, notifications, and automated actions in Fabric via read-only REST calls using `az rest` CLI. **Invoke this skill** whenever the user wants to: (1) list existing alerts in a workspace, (2) inspect how an alert or notification is configured, (3) read and decode an Activator/Reflex definition (ReflexEntities.json), (4) list rules, sources, and actions behind an alert, (5) understand why an alert fires or what action it takes. **Invoke this skill before answering questions** about an Activator/Reflex item in a Fabric workspace — the listing, lookup, and decoding workflows are part of this skill, not preamble to it. Triggers: "show my alerts", "what alerts do I have", "show me all activators", "inspect this alert", "show me the rule", "show me the action", "show me the source", "get reflex definition", "list activators", "list alerts", "list reflex items", "show activator items", "activator details", "find activator named", "inspect Power BI source", "metric definition behind this alert".
Reviews AI/ML systems for data privacy and governance risks including training data privacy, PII exposure in prompts and completions, data retention policies, model memorization risks, and regulatory compliance. Auto-invoked when reviewing systems that process personal data through LLMs, train or fine-tune models on user data, or deploy AI in regulated industries. Produces a structured assessment mapped to NIST AI RMF 1.0 and OWASP LLM02:2025 (Sensitive Information Disclosure).
When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "track conversions," "attribution," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For A/B test measurement, see ab-test-setup.
Recommend and generate appropriate data visualization charts using the GPT-Vis library. Supports two output modes — (1) Syntax mode, which generates Syntax or JSON configurations, and (2) Code mode, which generates complete runnable code. Supports 26 chart types.
Filter an existing audience or lead list against your ICP and split it into ready-to-sequence segments. Use when someone already has a list of people — an audience in their sales tool, a CSV or CRM export, event or webinar attendees, registrants, a Sales Navigator import, a newsletter or community export — and wants to know who is worth contacting. Triggers on: 'filter this audience against my ICP', 'who in this list matches my ICP', 'clean up this lead list', 'score these leads', 'qualify my signups', 'segment this audience', 'is my audience on-ICP', 'filter my webinar attendees', 'split this audience by ICP fit', 'remove the bad leads'. For SDRs, BDRs, RevOps, growth, demand gen and founders doing list qualification, ICP refinement, post-event follow-up or audience cleanup. Checks whether the data can support the ICP before filtering, sorts every lead into ICP match / needs review / no match, strips out your own team and competitors, and never silently drops anyone. Maintained by La Growth Machine.
Audit financial models and Excel workbooks for A-share analysis. Adapts the original audit-xls skill for Chinese financial modeling standards, CAS conventions, and A-share-specific checks. Triggers on "A股模型审计", "财务模型核查", "audit model China", "audit xlsx", "模型QC", or "check model [company]".
Implement Convex runtime features: HTTP actions, file storage, search (full text + vector), scheduling (crons + scheduled functions), and RAG patterns. Use for webhooks, uploads, search indexes, vectorSearch actions, and background workflows. Use proactively when users mention HTTP endpoints, files, search, embeddings, or cron/schedule. Examples: - user: "Add full text search" → define searchIndex + withSearchIndex query - user: "Upload files" → generate upload URL and persist storageId - user: "Vector search" → action with ctx.vectorSearch and doc fetch - user: "Run cleanup nightly" → cronJobs + function reference
Match an analytical question to the right Allium table, metric, dashboard, or realtime endpoint. Required when selecting a new data source for a query or analysis: define the intended meaning, compare schema candidates, test coverage, and record the fit and caveats before treating a source as correct. Run this before `allium-investigation` or any other analysis
Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook.
Display images and annotations for image processing, computer vision, and visual inspection. Use when displaying images with imageshow, creating image viewers with viewer2d, adding Regions of Interest (ROI) or annotations, overlaying masks or segmentations, streaming video frames, or building apps with image display.
Design, enforce, audit, and validate Power BI report themes through the pbir CLI. Invoke when a report uses a default or minimal theme, visuals have inconsistent formatting or many local overrides, or the user asks to create, copy, apply, standardize, rebrand, audit, or validate a theme; change theme colors or typography; define style presets; promote visual formatting into the theme; clear overrides; or improve theme compliance.
Power BI performance optimization for slow reports, models, and queries. PROACTIVELY activate for: (1) report is slow or visuals take forever to load, (2) DAX Studio and VertiPaq Analyzer profiling, (3) Performance Analyzer in Power BI Desktop, (4) optimizing slow DAX measures, (5) slow visuals diagnosis, (6) aggregations and composite-model tuning, (7) query reduction techniques (visual settings, top N), (8) model size reduction (cardinality, calculated columns, summary tables), (9) VertiPaq compression tuning, (10) Direct Lake performance and fallback rules, (11) large-dataset (10GB+) optimization. Provides: profiling workflow with DAX Studio, VertiPaq compression checklist, aggregation-table patterns, model-size reduction techniques, and end-to-end performance investigation playbook.
Graph database skills for Apache AGE on PostgreSQL. Covers the full lifecycle: deriving an ontology from structured or unstructured data with a human feedback loop, building the graph, and querying it with openCypher, natural language to Cypher, and graph augmented retrieval.
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.