'private data' 검색 결과

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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Up-to-date Zig programming language patterns for version 0.17.0-dev (0.16.0 stable APIs plus the 0.17 deltas). Use when writing, reviewing, or debugging Zig code, working with build.zig and build.zig.zon files, or using comptime metaprogramming. Critical for avoiding outdated patterns from training data - especially std.net→std.Io.net (requires Io instance), std.time timestamps removed (use clock_gettime), std.Thread.Mutex/Condition/sleep removed (use pthreads), std.crypto.random removed, build system APIs (root_module, Compile methods→Module methods), I/O APIs (buffered writer pattern), container initialization (.empty/.init), allocator selection (DebugAllocator), ArrayList now unmanaged by default, @typeInfo lowercase fields (.@"struct" not .Struct), and removed language features (async/await, usingnamespace). Also covers 0.17.0-dev deltas: b.args→run_cmd.addPassthruArgs(), std.gpu→std.spirv, @bitCast logical-bit (endian-agnostic) semantics, build configurer/maker split, and the zig-pkg/ package directory. Also covers quality tooling Zig does not ship: coverage with kcov (and why in-file tests wreck the denominator), detecting unused private functions (neither the compiler nor zlint's unused-decls finds them), duplicate detection with jscpd, zlint (NOT the same-named X.509 linter in Homebrew), and the built-in fuzzer whose testOne now takes *std.testing.Smith rather than []const u8.

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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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