Claude Code 플러그인
공개 Claude Code 마켓플레이스의 플러그인 165개입니다. 각 플러그인은 함께 설치되는 스킬, 슬래시 명령, 에이전트, 훅 또는 MCP 서버를 묶습니다.
필터와 일치하는 165개의 플러그인을 표시합니다. 필터 초기화
Internal BizOps domain. v2.8.0 ships 7 skills: orchestrator + process-mapper (BPMN/bottleneck/cycle-time, Lean+TOC) + vendor-management (scorecard+SLA+3rd-party risk, NIST SP 800-161/ISO 27036) + capacity-planner (Erlang-C queueing math for ops teams, NOT engineering) + internal-comms (ADKAR+Kotter 8-step, NOT marketing) + knowledge-ops (SOP+runbook+KB hygiene with 5W2H, context: fork) + procurement-optimizer (UNSPSC spend categorization + supplier consolidation). Orchestrator uses context: fork to route inquiries via Matt Pocock grill discipline (one question per turn, recommended answer, canon-cited challenge). Every SKILL.md ships a Forcing-question library section. 18 stdlib Python tools, 24+ reference docs. Distinct from business-growth (external sales) and c-level-advisor (strategic).
Per-deal-and-packaging Commercial domain. v2.8.0 ships 8 skills: orchestrator + pricing-strategist (model picker + Van Westendorp WTP + packaging) + deal-desk (deal scorer + discount approval routing + redline) + partnerships-architect (5-tier classifier + joint GTM + revshare modeler) + channel-economics (cost-to-serve + ROI + mix optimizer) + commercial-policy (data-backed discount matrix + exception flow + linter) + rfp-responder (Shipley structured RFP/RFI/RFQ + win-theme + winrate predictor, context: fork) + commercial-forecaster (4Q-weighted bookings + cohort NRR/GRR + funnel-confidence with mandatory assumption disclosure). Hard rules: pricing outputs model+range (never a single number), deal outputs route to named human approver (never auto-approve), forecast outputs surface conversion assumption, RFP never invents claims for GAP requirements. 21 stdlib Python tools, 28+ reference docs. Distinct from business-growth (sales execution), c-level-advisor/cro-advisor (strategic), fi
53 marketing skills for technical marketers and founders: CRO, copywriting, cold email, prospecting, SEO, AI SEO, paid ads, SMS, ad creative, video production, image generation, co-marketing, churn prevention, pricing, referrals, revenue operations, sales enablement, customer research, site architecture, comprehensive AARRR-structured marketing plans, public relations and earned media, offer design, event marketing and webinars, and more
120 marketing skills and 8 commands as an AI marketing staff — one plugin, portable skills on 70+ hosts, or an 8-bot team — and as a four-layer operating system: Narrative strategy; SEO/GEO, Organic Social, Email, Paid Ads, and Influencer channels; Product Launch orchestration; and a Protocol layer with seven append-only truth registries plus non-canonical working memory. Eight typed advisory frameworks (TALE, CORE-EEAT, CITE, STAR, ECHO, SEND, ROAS, RAMP) use machine-checkable auditor artifacts and immutable standalone runtime contracts. Keyless-first and zero-dependency.
PM utility skills: resume review, NDA drafting, privacy policy generation, and grammar/flow checking. Essential tools for product managers beyond core product work.
Core PM skills: PRD Template, Meeting Notes, Stakeholder Update, User Research Synthesis, Competitive Analysis, Word Doc Tracked Changes. The essentials every PM needs first.
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
Study companion for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org. Twenty chapter files, a glossary, patterns and a cheatsheet index the whole book, and a delta reference dates it against 2026 practice with per-claim confidence levels: double descent qualifying the U-curve, AdamW splitting weight decay from L2, transformers displacing Chapter 10's recurrence, diffusion growing out of Chapter 18's score matching. Four stdlib tools make it executable — a prerequisite-closed reading-path planner that refuses goals the book does not cover, a training diagnostic running Chapter 11's rules in priority order so a NaN is never reported as overfitting, a capacity planner that ranks 'shrink the model' last when overparameterized, and a parameter/FLOP/activation-memory calculator that refuses a stack whose shapes do not connect. A companion, not a compilation: the book is copyrighted, so nothing here reproduces its text.
Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent skills: a master SKILL.md with core frameworks and a topic index, on-demand chapter files, a glossary, a patterns file, and a decision cheatsheet. Ships 4 stdlib-only tools (multi-format extractor with invisible-Unicode sanitization, four-family generated-skill validator covering frontmatter/safety/budget/index, pre- and post-flight token budget estimator with a worth-converting verdict, and a plugin emitter that wraps a compiled skill as an installable claude-skills package behind a rights gate), 5 references citing 7-8 sources each, a cs-book-to-skill agent, and /cs-book-to-skill + /cs-book-to-plugin commands. Derived from virgiliojr94/book-to-skill (MIT).
Engineer an agent's forgetting, not just its remembering. Four deterministic stdlib scripts implement the four lenses of agent memory: a cost profiler that splits construction from query spend and reports cost per correct answer (construction energy exceeds total query energy across 300 queries in the Stanford characterization); an architecture picker that scores the four paradigm families — long-context, flat RAG, structure-augmented RAG, agentic — disqualifies on hard constraints, names the cost the winning choice makes you pay, and refuses to pick when the top two tie; a density auditor that classifies every record in a memory directory or JSONL export as FACT / SKILL / LOG / PROSE, finds near-duplicates, and flags stale wording; and a forgetting-policy linter that fails any design with no forgetting rule. Ships cs-memory-engineer agent, /cs-memory-engineering and /cs-forgetting-audit commands, 4 references, and a seven-question forcing worksheet.
Get a defense supplier ready for a CMMC 2.0 Level 2 assessment. Three deterministic stdlib scripts: an SPRS scorer that weights all 110 NIST SP 800-171 Rev 2 requirements per 32 CFR 170.24 and blocks gaps that can never go on a POA&M; a POA&M closeout tracker that checks every deferred gap against the 180-day Conditional status deadline and the annual affirmation calendar; and a scope classifier that sorts the asset inventory into the 170.19 categories and blocks on assets missing from the SSP or cloud providers holding CUI without FedRAMP. Ships cs-cmmc-assessor agent, /cs-cmmc-readiness and /cs-sprs-score commands, 3 cited references and a readiness sign-off.
Cross-journal author workflow toolkit (11 skills): pick the venue (journal-match runs tools/match_venues.py over a generated index of 743 venues with a resubmission-ladder graph, and is measured against a held-out gold set), cost the submission ladder in months and probability of placing, verify an unfamiliar venue against primary sources before submitting, reframe a manuscript from one venue to another, run the analysis through the StatsPAI / Stata MCP execution bridge, self-check submission readiness, score desk-reject risk against the target's own documented triggers, rehearse a calibrated referee panel, draft the point-by-point response, and assemble a Data-Editor replication package. Venue-neutral; reads each target pack's skills + official-source-map for the venue bar and live facts.
academic
Core AIWG utilities for context regeneration and workspace management.
Grade an agent setup from real conversation history — a rebuild of warpdotdev/common-skills' skill-doctor (MIT). Harvests recent local Claude Code and Codex sessions scoped to one repo, condenses and secret-redacts transcripts (12-pattern redactor, chmod-0600 artifacts, nothing uploaded), has the agent judge each transcript against two verbatim-preserved rubrics (efficiency, code quality — labels only), then runs a deterministic aggregation gate that derives every number from the label tables, refuses scores for unsampled sessions and suggestions that cite no scored session, and renders one self-contained zero-JS HTML report (dark-mode, print-to-PDF). Proposed skill edits stay staged as diffs until an explicit per-skill yes; zero suggestions is a valid, reportable success. Ships cs-skill-retro agent, /cs-skill-retro command, 3 stdlib tools, 3 references citing 7 sources each.
Pressure-test a business idea before you build it. Convenes a 5-angle adversarial panel — The Critic (what kills this?), The Champion (the 10x upside?), The Analyst (does the logic hold?), The Investigator (what does the market say?), The Customer (would I actually pay?) — fired in parallel as independent reviewers, then a Judge synthesizes one GO / RESHAPE / KILL verdict with explicit confidence and the cheapest 48-hour test to de-risk it. Never averages the scores: a weighted synthesizer with demand/fatal-flaw/logic veto gates produces the call, backed by deterministic stdlib tools.
GTD weekly-review loop. Scans the workspace for open loops (unchecked boxes, TODO/FIXME, stale files), walks the three-phase GET CLEAR / GET CURRENT / GET CREATIVE checklist with a refusal gate (review is never COMPLETE while a mandatory GET CURRENT step is missing), and audits commitments for stalled / no-next-action / someday candidates with a 0-100 health score. Fills the periodic-review gap from audit/productivity-2026-07.
Disciplined multi-source meta-research for high-stakes questions — the heavyweight alternative to the fast research router. 9-phase pipeline (reframe into falsifiable hypotheses, plan, capability discovery, parallel sub-agent fan-out, score & triangulate, synthesize + adversarial pass, verify, refresh targets). Triangulates every thesis against >=3 independent differently-typed sources; per-source files with verbatim quotes; never fabricates a citation. Auditable, reusable folder + delta-update refresh protocol. Contributed via PR #851.
Knowledge base compiled from OpenAI's Spinning Up in Deep RL (MIT, Joshua Achiam) by engineering/book-to-skill. A resident core carries the RL optimization problem, the model-free taxonomy, the policy-gradient template with its five valid weights, the safe-step family (VPG to TRPO to PPO) and the overestimation family (DDPG to TD3 and SAC); 20 on-demand chapters cover key concepts and MDPs, the algorithm taxonomy and model bias, the policy gradient derivation with the log-derivative trick and EGLP lemma, Achiam's researcher essay, the key-papers topic map, the exercises including the silent DDPG broadcasting bug, the benchmark parity disclosure, one chapter per algorithm, and the logger/MPI/ExperimentGrid utilities. Ships a glossary, a patterns file with 16 techniques, a decision cheatsheet with thresholds, a cs-spinning-up-deep-rl agent and /cs-spinning-up-deep-rl. Structured study notes, not a reproduction of the source.
Recruiting & talent-sourcing skills: Boolean Search Builder, Recruiter Outreach, Interview Question Bank, Candidate Scorecard, Offer Letter, and Sourcing Strategy. Source, assess, and close candidates — structured and fair.
Customer Success skills: Customer Health Scorecard, QBR Deck, Escalation Brief, Churn Analysis, Renewal Playbook, Customer Success Plan. Score health, build QBRs, write escalation briefs, plan renewals with commercial strategy and objection responses, and build joint success plans with milestones and mutual commitments.