'does' 검색 결과

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

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Counts and compares blog posts across a target and competitors, audits content freshness via sitemap lastmod dates, and maps competitor organic keywords (US, non-branded, informational) against the target to surface ranking gaps. Use when asked to compare blog counts, content volume, publishing cadence, content freshness, keyword mapping, keyword gap analysis, or competitor keyword reports — e.g. "how many blog posts does X have vs Y", "how fresh is content on X", "where does [target] rank for [competitor] keywords", "keyword gap between X and Y". Works from company names alone. Always use for blog comparison, freshness audits, and keyword mapping tasks.

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What the desk does when something goes wrong on Hyperliquid - unknown send results, unexpected fills or positions, unprotected positions, stuck or orphaned orders, API outages, rate limiting, and suspected API wallet compromise. Contain first, reconcile from the exchange record, act only through approved tickets, then review. Use the moment anything does not match the ticket.

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Neo4j JavaScript/TypeScript Driver v6 — driver lifecycle, executeQuery, managed transactions (executeRead/executeWrite), session.run, Integer handling, JSON serialization, record access, async/await patterns, TypeScript types, error handling, and connection setup for Node.js and browser. Use when writing JS/TS code that connects to Neo4j — neo4j.driver(), executeQuery, executeRead, executeWrite, session.run, neo4j.int, record.get, Integer, BookmarkManager, bolt://, neo4j+s://. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver version migration — use neo4j-migration-skill.

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Build and configure a GraphQL API backed by Neo4j using @neo4j/graphql v7 (current) or v5 (LTS). Covers Neo4jGraphQL constructor, getSchema(), assertIndexesAndConstraints(), type definitions with @node, @relationship (IN/OUT/UNDIRECTED), @cypher for custom resolvers, @authorization/@authentication for JWT/JWKS security, auto-generated queries/mutations, OGM programmatic access, subscriptions via CDC, and Apollo Federation. Use when writing typeDefs, securing fields, or wiring Neo4j to Apollo Server. Does NOT handle raw Cypher outside resolvers — use neo4j-cypher-skill. Does NOT cover Spring Data Neo4j entity mapping — use neo4j-spring-data-skill.

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Programmatic security management in Neo4j — RBAC/ABAC, user lifecycle (CREATE/ALTER/DROP USER), role lifecycle (CREATE/GRANT ROLE/DROP ROLE), privilege grants and denies (GRANT/DENY/REVOKE on graph, database, DBMS), property-level access control, sub-graph access control, SHOW PRIVILEGES inspection, and auth provider config reference (LDAP, OIDC/SSO). Use when an agent needs to manage users, roles, or privileges programmatically via Cypher on the system database. Does NOT handle Cypher query writing — use neo4j-cypher-skill. Does NOT handle cluster ops or backups — use neo4j-cli-tools-skill. Property-level security and ABAC require Enterprise Edition.

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Manages Neo4j Aura Agents via the v2beta1 REST API — create, list, get, update, delete, and invoke Aura agents backed by an AuraDB instance. Use when configuring Aura Agent tools (CypherTemplate, SimilaritySearch, Text2Cypher), setting system prompts, deploying agents to REST or MCP endpoints, invoking agents with natural language queries, or generating evaluation datasets (max 50 questions) for the Aura Agent evaluation feature. Covers OAuth2 auth, organization/project scoping, tool parameter schemas, and InvokeAgentResponse format. Does NOT cover AuraDB instance provisioning — use neo4j-aura-provisioning-skill. Does NOT cover vector index creation — use neo4j-vector-index-skill.

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Neo4j .NET Driver v6 — IDriver lifecycle, DI registration (singleton), ExecutableQuery fluent API, ExecuteReadAsync/ExecuteWriteAsync managed transactions, IResultCursor (FetchAsync/ ToListAsync), record value access (.Get<T>/As<T>), null safety, UNWIND batching, temporal types, await using, EagerResult, object mapping, CancellationToken, error handling, and common traps. Use when writing C# or .NET code connecting to Neo4j. Also triggers on Neo4j.Driver, IDriver, ExecutableQuery, ExecuteReadAsync, ExecuteWriteAsync, IResultCursor, IAsyncSession, or any Bolt/Aura work in .NET/C#. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver version upgrades — use neo4j-migration-skill.

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Generates, optimizes, and validates Cypher 25 queries for Neo4j 2025.x and 2026.x. Use when writing new Cypher queries, optimizing slow queries, graph pattern matching, vector or fulltext search, subqueries, or batch writes. Covers MATCH, MERGE, CREATE, WITH, RETURN, CALL, UNWIND, FOREACH, LOAD CSV, SEARCH, expressions, functions, indexes, and subqueries. Does NOT handle driver migration or API changes — use neo4j-migration-skill. Does NOT cover DB administration or server ops — use neo4j-cli-tools-skill.

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Covers the Neo4j Go Driver v6 — driver lifecycle, ExecuteQuery, managed and explicit transactions, session config, error handling, data type mapping, and connection tuning. Use when writing Go code that connects to Neo4j, setting up NewDriver or ExecuteQuery, debugging sessions/transactions/result handling, or working with neo4j-go-driver v5→v6 migration. Triggers on NewDriver, ExecuteQuery, SessionConfig, ManagedTransaction, neo4j-go-driver. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver version migration steps — use neo4j-migration-skill.

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Use Neo4j GenAI Plugin ai.text.* functions and procedures for in-Cypher embedding generation, text completion, structured output, chat, tokenization, and batch ingestion. Covers ai.text.embed(), ai.text.embedBatch(), ai.text.completion(), ai.text.structuredCompletion(), ai.text.aggregateCompletion(), ai.text.chat(), ai.text.tokenCount(), ai.text.chunkByTokenLimit(), and provider configuration for OpenAI, Azure OpenAI, VertexAI, and Amazon Bedrock. Requires CYPHER 25. Replaces deprecated genai.vector.encode(). Use when writing pure-Cypher GraphRAG, embedding nodes in-graph, generating structured maps from prompts, or calling LLMs inside Cypher queries. Does NOT handle neo4j-graphrag Python library pipelines — use neo4j-graphrag-skill. Does NOT handle vector index creation/search — use neo4j-vector-index-skill.

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This skill should be used before answering "does Genesis have X", "does Genesis lack X", auditing Genesis capabilities, comparing Genesis to an external system, or reviewing/summarizing the architecture. It routes to the canonical judgment-layer subsystem map so audits start from the map, not from a cold grep. Also fires after changing a subsystem's capabilities, to keep the map current.

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Foundational voice authority and AI humanizer — writes content in the user's authentic voice with built-in AI detection, and supports stealth / anti- attribution writing (forum personas, anonymous posts, "write as not-me"). Use when asked to write/draft/generate content, invoke /voice, /write-as-me, or /humanize, run voice calibration, check "does this sound like me?", "make this sound human" / "de-AI this", "write a forum post as [persona]", or run AI detection ("does this sound like AI?", "check for AI patterns", "anti-slop check"). Do NOT use this skill for code, technical docs, or any output the user has not asked to be written in their voice — code styling defers to the separate code-voice skill.

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Use when the user wants to pressure-test a product, internal-tool, or OSS concept against Amazon's Working Backwards PRFAQ gauntlet before committing to a spec. Triggers on: "work backwards", "write a PRFAQ", "press release first", "is this idea worth building", "pressure-test this concept", "filter this before brainstorm", "is this a real product". Also catches solution-first pitches ("I want to build X that does Y") and technology-first pitches ("use AI to...") that need customer-first filtering. Produces a binary pass/fail verdict, not a polished doc. Hardcore coaching — direct, skeptical, concrete. On pass, hands off to brainstorm-beagle with a concept brief. Does NOT write code, plan implementation, scaffold projects, or draft specs.

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Use when comparing two or more code implementations against a spec or requirements doc. Triggers on "which repo is better", "compare these implementations", "evaluate both solutions", "rank these codebases", or "judge which approach wins". Also covers choosing between competing PRs or vendor submissions solving the same problem. Does NOT review a single codebase for quality — use code review skills instead. Does NOT evaluate strategy docs — use strategy-review. Requires a spec file and 2+ repo paths.

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Use when the user wants web research: gathering cited, multi-angle evidence on a specific question. Triggers on: "research X for me", "do web research on", "look up sources for", "find citations for", "gather evidence on", "what does the web say about X". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups ("find this function", "search the repo"), local file search, LLM-as-judge evaluation, or paywalled/auth-gated scraping. Produces a written plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced claims.

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Use when the user asks to write, draft, or edit a standalone piece of prose — an article, essay, blog post, tweet, thread, newsletter, announcement, email, pitch, or other copy — and the request does not already name "Hedgehog". Length is not the test: a tweet qualifies the same as an essay. Does not apply to a question about existing code, a bug, a one-off script, or a request that already names Hedgehog (that goes to the `hedgehog` skill instead) or a project that already has `.hedgehog/` (its own installed skills own that session).

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Use this skill when an engineering team needs a secure development policy, or has one that does not match how code really ships, and asks "write our secure SDLC policy", "secure development policy from our CI", "document our code review and scanning for the audit", "what does our pipeline already enforce", "change management for engineers" or "secure coding policy for SOC 2 or CRA". Reads the repositories and pipeline definitions, inventories what is actually enforced (reviews, checks, scanners, deploy gates, dependency and secret controls), and writes a policy whose every "must" points to the place it is enforced, with gaps listed as decisions.

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Use this skill when a company has no incident response plan, has one copied from a template that names teams it does not have, or an auditor, customer or insurer asks for it, and the team says "write our incident response plan", "IR plan", "security incident procedure", "who does what in an incident", "incident playbooks", "contact tree for incidents" or "our plan failed in the last incident". Drafts a plan sized to the company with roles and deputies, a severity scale, a contact tree with an out-of-band channel, one-page playbooks for the likely scenarios, evidence handling and a notification decision step, plus a one-page quick reference card.

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Use this skill when a published privacy notice may no longer match what the company does, or someone asks "is our privacy policy accurate", "check our privacy notice against the RoPA", "privacy notice review", "Article 13 and 14 check", "does our website privacy policy cover our vendors and cookies" or "update the privacy notice for the new product". Maps every collection point, compares each notice with the processing record, the vendor list and what the site and product actually collect, classifies what is missing, wrong, vague or stale, and drafts a redline plus the practice fixes that a notice edit cannot solve.

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Use this skill when a company must work out where each of its AI systems sits under the EU AI Act, and asks "is this high-risk", "classify our AI systems", "AI Act risk tier", "are we a provider or a deployer", "does Annex III apply to us", "is this a prohibited practice", "what does the AI Act mean for our chatbot" or "which AI Act obligations do we have". Tests each system, one at a time, for scope, role, prohibited practices, the two high-risk routes, the narrow exemption, transparency duties and general-purpose models, and writes a reasoned classification record per system plus a summary table of resulting obligations to confirm with whoever owns legal interpretation.

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Each routine does one thing and does it well - extract when routines have multiple responsibilities

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Extract the conceptual essence of a repository as skills, agents, and teams — the project's roles, procedures, and coordination patterns expressed as agentskills.io-standard definitions. Reads an arbitrary codebase and produces generalized definitions that capture WHAT the project does and WHO operates it, without replicating HOW it does it. Use when onboarding to a new codebase and wanting to understand its conceptual architecture, when bootstrapping an agentic system from an existing project, when studying a project's organizational DNA for cross-pollination, or when creating a skill/agent/team library inspired by a reference implementation.

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Audits and scores Claude Projects using a six-dimension Scorecard with anchored 1-5 rubrics and detects seven structural anti-patterns. When global layer info is provided, adds cross-layer alignment findings. Use when user says "audit my project," "review my custom instructions," "score my project," "evaluate my Claude project," "improve my system prompt," "what's wrong with my project," "why is my project underperforming." Also trigger on symptom-phrased: "my project doesn't work right," "Claude is inconsistent in my project," "my Project used to work and now doesn't." Also use when the user pastes Custom Instructions asking why output is poor or generic. Do NOT use when the user's primary request is a global-layer audit (use rootnode-global-audit if available), single-prompt evaluation (use rootnode-prompt-validation if available), or Memory-only optimization (use rootnode-memory-optimization if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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