154 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 154 plugins that match these filters.
claude-code-workflowswshobson/agents1
ai-driven-developmentCodeAlive-AI/ai-driven-development1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplaceEmail-workflow skill pair: inbox-setup builds your taxonomy/KB; inbox-triage classifies + drafts (drafts-only, never auto-send). KB-file contract between them. Path-B from megaprompts 06+07.
AI/ML engineering skills for shipping AI features responsibly: Model Card, AI Eval Plan, RAG Design Doc, Agent Spec, Dataset Datasheet, AI Feature PRD, LLM Cost & Latency Budget, Prompt Optimizer, Eval Rubric Designer, RAG Architecture Review, LLM Guardrails Spec, Agent Design Review, and Model Selection Advisor.
AI image generation with creative workflow orchestration, prompt engineering, and curated inspiration library via MCP server
Answer questions about past agent runs from the recording, not from memory. Three read-only stdlib scripts over the session transcripts Claude Code and Codex already write: a finder that locates the run by repo, time window, touched file or command text; a timeline that numbers every step with its exit code, lists every file changed (flagging changes the agent never mentioned) and walks back from any step with each causal edge labelled recorded or inferred by a named rule; and a claim checker that tests a summary's claims (ran, passed, edited, not-edited, read) against the run and catches tests that passed before a later edit and exit codes that belong to the last command of a pipe. Secrets are always redacted. A UserPromptSubmit hook gives the agent this session's transcript path when a prompt asks about past work. Ships cs-run-forensics agent, /cs-run-forensics and /cs-check-claims commands and 3 cited references.
Marc Andreessen-mode decision and productivity skill. Market-first operator that pressure-tests ventures/ideas/features/bets (market > team > product; product/market fit is the only milestone; bias to build) and runs the 3x5-card + Anti-Todo routine. Fixed anti-sycophancy operating prompt: counterargument first, no disclaimers, explicit confidence levels, no capitulation. Issues hard verdicts backed by deterministic stdlib tools.
A four-tier memory ladder for Claude Code where promotion is earned by recurrence, not asserted by confidence. L0 raw transcripts are never injected; L1 candidate atoms are gitignored and recalled on lexical relevance per prompt; L2 project context loads each session start; L3 stable persona is always loaded. L1 to L2 needs three distinct sessions spanning two distinct calendar days (a stated claim needs two; a verified claim is the only single-observation path); L2 to L3 needs two projects and thirty days. Two gates refuse rather than guess: a claim altered by the redaction pass never promotes on evidence alone, and a contradicted claim freezes until a human resolves it. Three hooks run the loop unattended and every one fails open. Nothing reaches a committed CLAUDE.md without an explicit human adopt. Ships 5 stdlib scripts, 3 hooks, a cs-memory-curator agent, /cs-memory, a JSON schema, and a 69-check validator. Concept from TencentCloud/TencentDB-Agent-Memory (MIT); no upstream code
Prove an agent, prompt, model or tool change did not make the agent worse. Three deterministic stdlib scripts: a trajectory checker that grades tool-call paths (strict / unordered / subset / superset match modes, argument matching, forbidden tools that block in every mode, call ceilings); a flake detector that classifies each case as stable or flaky from repeated trials and reports pass@k and pass^k with Wilson intervals; and a paired regression gate that averages trials per case, tests per-case differences with a t-based CI and an exact one-sided McNemar test, and blocks the merge on a significant drop, a critical-case regression, a dropped case, or a quarantine entry without owner and expiry. Ships cs-eval-gatekeeper agent, /cs-agent-evals and /cs-eval-gate commands, 3 references, and a CI job example.
Operate AI agents and LLM features in production: prompt regression suites, model migration plans, context-engineering reviews, agent incident postmortems, and observability specs — plus the pm-ai evaluation and cost skills they build on.
Brain-dump-to-action workspace skill. Routes vague captures into discoverable actions via classify→cluster→connect→clarify intake. Path-B from megaprompt 05.
Light-prompt reflection skill. Single forcing question + structured journal capture. Path-B sibling of capture from megaprompt 08.
Single-file HTML landing-page generator with 4 design styles, brand palette validation, GSAP animation patterns, kebab-slug URL hygiene. Path-B from megaprompt 04.
Multi-source recency research. Reddit/HN/X/web sentiment + trending. Research-pack convention (1 q/sec, three-count tracking). Path-B from megaprompt 01.
Academic literature orientation skill. PICO/SPIDER frameworks, systematic review structure, 8-section DOCX guide. Research-pack convention. Path-B from megaprompt 09.
NIH grant-funding intelligence skill. RePORTER/NOSI/study-section navigation, R01/R21/K-award strategy. Research-pack convention. Path-B from megaprompt 11.
Decision-grade entity research. Due-diligence/background-check/competitor-prep with tier-weighted verdict + citation tracker. Research-pack convention. Path-B from megaprompt 02.
Patent prior-art + IP landscape skill. FTO/novelty/family-resolver via 3-pass Jaccard heuristic. Research-pack convention. Path-B from megaprompt 12.
Course supplementary-reading skill. Topic-grouper + bundled Node.js DOCX generator for syllabus-anchored reading lists. Research-pack convention. Path-B from megaprompt 10.
Google NotebookLM browser-automation skill. 4 actions (read/extract, add-source, Studio outputs, create notebook). Screenshot-first + find-before-click + fire-and-notify async discipline. Path-B from megaprompt 03.
Research orchestrator (hybrid router + fallback). Deterministic SIGNALS classification routes to 6 specialists (pulse/litreview/grants/dossier/patent/syllabus) at >=2 signals, else runs own 8-step plan-decompose-search-synthesize-cite fallback. Routing transparency mandatory. Path-B from megaprompt 13.
An umbrella collection of 23 skills + 1 hook for AI-driven development: agent self-configuration (MCP / hooks / settings / skills / plugins / cross-agent repository readiness / safe CLI installation), engineering practices (UX review and accessibility, maintainable complexity, prompt engineering, FPF problem solving, bug-fix protocol, planning gate, repository-history investigation, repository activity summary, C# refactoring), AI infrastructure (OpenRouter endpoint ranking and routing), research & docs (Semantic Scholar deep research, URL-to-Markdown, ubiquitous-language thesaurus), macOS & Windows health & cleanup, and niche utilities (clipboard, Windows QA). Plus a Claude Code Bash safety hook.
