104 skills · sorted by relevance
Use when a macOS app needs a TCC permission or touches private data — the map of which API, Info.plist key, and entitlement each permission needs, pre-prompt explanation patterns, denied-state recovery with System Settings deep links, and honest privacy copy.
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Local, private capture of medical data: diagnoses, symptom histories and examination plans. No BACH origin — custom design with its own SQLite store. Strictly local, no cloud transfer.
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Use when the user asks to "figure out where our direct traffic really comes from", "measure dark social", "add a how-did-you-hear-about-us field", or "show social drives signups without click data"; produces a share-link/UTM hygiene spec for owned share surfaces, a self-reported attribution field design that replaces an existing form field (free-text first, coded later), a GA4 direct-traffic decomposition read (deep-URL directs, mobile-app skew, private-push correlation) with every derived number hard-labeled Estimated/proxy, and a branded-search-lift proxy from GSC plus Wikipedia pageviews — the declared dark-social method behind ECHO O2. Not for paid-channel attribution reconciliation (platform-claimed vs analytics conversions) — use attribution-reconciler. 暗社交归因/直接流量分解/自报来源字段/分享链路UTM
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Audit paid-ad landing pages for message match, mobile experience, performance, accessibility, trust, forms, consent, tracking, security, and conversion friction. Use for landing-page audit, post-click experience, LP audit, conversion-rate optimization, form optimization, ad-to-page message match, redirects, blocked navigation, or requests involving private, loopback, link-local, or metadata IP destinations.
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Write Estuary derivations in Python — async-generator transforms, Pydantic-typed source/output, optional persistent state, and dependency installation via uv. Use for ML/embeddings, async API calls, or any transform where SQL and TypeScript are awkward. Derivations add complexity and cost (and Python derivations require a private/BYOC data plane) — confirm the user wants a Python derivation before reaching for this. Use when user says "python derivation", "write a derivation in python", "embed with a python derivation", "ML derivation", "call an API from a derivation", or anything mentioning model2vec / huggingface / pydantic in a derivation context.
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Use for Nauthilus authentication and identity-provider work touching OIDC, OAuth2, SAML, MFA, TOTP, WebAuthn, recovery codes, LDAP-backed identity, browser login and consent flows, token/session/flow state, `private_key_jwt`, introspection, discovery metadata, endpoint-specific client authentication, and security-sensitive auth tests.
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Fetch Airbnb income estimate (ADR, occupancy, monthly revenue) for any area using the official Airbnb GraphQL API — the same data the Airbnb host simulator shows. Input: station/area name. Output: per-night rate, avg nights, monthly estimate for entire_home and private_room.
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Publish agent skills AND MCP servers to every marketplace, plugin directory, and registry — security-scan for private data, validate with `gh skill`, cut a release, wire the Claude /plugin and Codex marketplaces, publish an MCP server to the official MCP Registry (mcp-publisher + server.json), and prep the curated / monetized stores (Buda Marketplace, Agensi, OpenClaw ClawHub) and review-gated directories (ChatGPT App Directory, Anthropic Connectors + Desktop Extensions/.mcpb). Use when the user wants to publish, release, list, 上架, or distribute agent skills, plugins, or MCP servers to skills.sh / SkillsMP / Claude Code / Codex / the MCP Registry.
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