'first run' 검색 결과

Remove AI-generated code smells (slop) from branch changes or an explicit file list. Locks behavior with regression tests FIRST, then runs categorized cleanup via parallel `deep` agents in batches of 5, then verifies with quality gates. Covers 10 slop categories including performance equivalences, excessive complexity (object annotations, if/elif variant chains), and oversized modules (250+ pure LOC with mandatory modular refactoring). MUST USE when the user asks to "remove slop", "clean AI code", "deslop", "clean up AI-generated code", "remove AI slop", or wants to clean up AI-generated patterns from recent changes. Triggers - "remove ai slops", "clean ai code", "deslop", "cleanup AI generated", "remove AI slop", "clean up AI-generated code", "strip slop", "ai-slop cleanup".

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White-box security audit. Blue-teamer and lead red-teamer run in parallel isolation for an independent first pass — neither sees the other's output during reconnaissance. A synthesis step categorizes findings into four prescriptive buckets (anchoring-suppressed, convergent, blue-flagged-unverified, divergent), producing a unified target list. Focused red-teamers then deep-dive each target. Iterates when exploit chains are discovered. Heavy and thorough by design. Advisory only — produces findings and proposes tickets; does not implement remediation.

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Good-faith divergent brainstorming for achieving a goal. Validates assumptions, then spawns brainstormers running different techniques (first-principles, working-backwards, lateral, analogical, constraints-shift, etc.) in isolation, and synthesizes the pool into a report of standouts, reasonable ideas, and hybrid combinations. Produces feedback only — no code, no tickets, no artifacts.

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Use when the user wants local voice transcription instead of OpenAI Whisper API. Switches to whisper.cpp running on Apple Silicon. WhatsApp only for now. Requires voice-transcription skill to be applied first.

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Debug by naming one observed failure, patching the smallest owner, and rerunning the same evidence path.

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Write or audit technical text against ASD-STE100 Simplified Technical English so a tired, non-native reader understands it on the first pass: 20-word procedural and 25-word descriptive sentence limits, imperative steps, condition before command, one word for one meaning, and only the approved modals can/will/must. Use for READMEs, runbooks, procedures, error messages, release notes, incident reports, API guides, UI copy, and agent instructions. Trigger on: "STE", "Simplified Technical English", "ASD-STE100", "controlled language", "plain English", "make this clearer", "write for non-native readers", "prep this for translation", "cut the fluff", or any request to check text for compliance. Prefer this over general copy-editing whenever the text instructs, documents, or warns.

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Write, rewrite, review, and organize developer-facing documentation for web software projects. Use when creating or improving README files, docs homepages, quickstarts, tutorials, how-to guides, API/reference pages, conceptual explanations, migration guides, or troubleshooting content for frontend, backend, full-stack, SDK, API, or framework-based web products. This skill applies strong information architecture, task-first page structure, clear voice, runnable examples, version and prerequisite hygiene, accessibility rules, and docs-as-code maintenance habits. Do not use it for marketing copy, legal text, or non-technical customer-support articles.

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Evidence-first ECC Tools burn and billing audit workflow. Use when investigating runaway PR creation, quota bypass, premium-model leakage, duplicate jobs, or GitHub App cost spikes in the ECC Tools repo.

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Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.

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Use with DecisionsAI when a ticket or workflow needs internet research — social posts, articles, video subtitles, GitHub, RSS, or competitor scans. Routes through Agent Reach upstream tools; run agent-reach doctor first.

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Test-driven development with a red-green-clean loop, running mix credo on the whole project at the end of every vertical slice so standards violations are fixed in the slice that introduced them instead of piling into a refactor at the end. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.

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Delegate implementation work to a dedicated implementer subagent, then review its diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants a separate model to write code, mentions handing off / delegating implementation, asks to work through a plan or spec unit-by-unit with a subagent doing the coding, or wants a review-and-merge loop wrapped around delegated output — and also when resuming such a loop ("keep going", "next unit", "继续下一个"). It encodes constraints that are expensive to rediscover: the implementer self-reports success, must not run the full test suite by default, must not touch git, and its report is a claim rather than evidence. Cursor port of implementation-loop. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the cursor-engineering-mode skill (it ships in this same plugin).

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Delegate implementation to Codex or to a sandboxed Claude Code (`claude -p`), have a model from the other vendor review the diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants Codex or a sandboxed Claude to write code, mentions handing off / delegating implementation to one of those backends, asks for a cross-vendor review of delegated code, asks to work through a plan or spec unit-by-unit with an implementation backend doing the coding, or wants a review-and-merge loop wrapped around delegated output — and also when resuming such a loop ("keep going", "next unit", "继续下一个"). It encodes constraints that are expensive to rediscover: the implementer runs in the real environment behind backend-specific git and publication boundaries, must not be pointed at a full test suite by default, and its self-report is a claim rather than evidence. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the engineering-mode skill when it is installed.

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Internal utility for the skills library itself — opt-in, local-first, privacy-respecting usage telemetry and update checks. Provides version checking, usage logging, and usage reporting for the skills in this repo. Use only when asked to view skill usage stats, configure telemetry opt-in/out, wire a skill to log its own runs, or check for skill updates.

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Diagnoses and fixes bugs, type/lint errors, CI failures, and runtime errors, root-cause first. NOT for investigation without a fix (mk:investigate) or build-only compile errors (mk:build-fix).

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Chief Security Officer mode. Infrastructure-first security audit: secrets archaeology, dependency supply chain, CI/CD pipeline security, LLM/AI security, skill supply chain scanning, plus OWASP Top 10, STRIDE threat modeling, and active verification. Two modes: daily (zero-noise, 8/10 confidence gate) and comprehensive (monthly deep scan, 2/10 bar). Trend tracking across audit runs. Use when: "security audit", "threat model", "pentest review", "OWASP", "CSO review".

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First-run setup wizard for the Recruiter Skills Pack. Creates config, verifies API keys, shows available skills.

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Autonomous driver loop for ExploitHunter vulnerability-research campaigns. Runs breadth-first waves of research lanes on rented hosts with no per-request human approval, steers lanes via the shared Investigation Graph (demoting dead ends, respawning on high-signal priorities), saturates host capacity, and enforces wave/budget/safety discipline. Use when driving a multi-target bug-hunting campaign, launching parallel research lanes, or resuming a campaign from a state snapshot.

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Order and interpret lipoprotein(a) [Lp(a)] measurement at least once in a lifetime, apply the risk-enhancer threshold (≥125 nmol/L or ≥50 mg/dL), and run cascade screening of first-degree relatives for premature ASCVD, familial hypercholesterolaemia, or elevated Lp(a) per the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers the Class 1 lifetime measurement, how elevated Lp(a) affects LLT initiation and intensification, the cascade screening indications, the interaction of Lp(a) with ASCVD risk estimation, and current therapeutic limitations. Use when a clinician asks when to check Lp(a), how often to repeat Lp(a), elevated Lp(a) what next, treatment for high Lp(a), should I screen my patient's family, Lp(a) and statins, cascade screening indications. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.

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Phase 10.5 — move the slug's workflow artifacts (intake, scout, research, spec, approvals, swarm state, security reports, rendered diagrams) to docs/archive/<YYYY-MM-DD>/<slug>/. Runs before /commit so the committed tree is clean of work-in-flight files. workflow.json stays live and gets archived as the first step of /commit.

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Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local markdown), triage label vocabulary, and domain doc layout. Run before first use of `to-issues`, `to-prd`, `triage`, `diagnose`, `tdd`, `improve-codebase-architecture`, or `zoom-out` — or if those skills appear to be missing context about the issue tracker, triage labels, or domain docs.

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Use for read-first Amazon Sponsored Products optimization, product-aware growth, preflight readiness, and post-change monitoring reviews that can run standalone from static exports or use Rocketcart MCP as an optional Amazon Ads plus product-intelligence layer. Guides Codex to inspect Rocketcart profiles, live SP campaigns, product ads/ASIN context, category rank/BSR movement, competitor signals, product readiness, budget and targeting drift, snapshots/changelogs, and proposed approval-gated action rows without executing writes by default.

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Deep enrichment for community-sourced enterprise PROSPECTS (the 🎯 Prospective enterprise customers subsection). For each prospect, resolve their LinkedIn from their GitHub self-linked accounts FIRST (search only if none is self-linked), verify the employer matches, capture their full name, then list the company website + company size (ARR / latest funding round / employee count). Runs as a general-purpose subagent (many web searches) so the orchestrator's context stays small. Invoked by weekly-report (enterprise section) and the enterprise skill.

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Generate the ≤10-minute Loom walkthrough script for a completed Weekly Community Signal report — a plain spoken briefing that dives straight into what the team needs to know, walking the report top to bottom (CopilotKit page first, then AG-UI in the same order). Straightforward and factual, NOT a radio show or a performance; no hype opener, no blame framing. Runs after every report (invoked by weekly-report) and on "loom script", "walkthrough script", "record the loom", "narrate the report".

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