16 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 16 plugins that match these filters.
planning-with-filesOthmanAdi/planning-with-files1
claude-code-workflowswshobson/agents1
claude-toolboxserpro69/claude-toolbox1
swe-marketplaceandisab/swe-marketplace1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplaceEnterprise / cross-functional Research Operations domain — the managed counterpart to the academic research/ domain. v2.9.0 ships 5 skills: orchestrator (context: fork), clinical-research (protocol synopsis, endpoint selection, sample-size/power for means/proportions/survival, phase-gate feasibility), research-finance (R&D budgeting with F&A split, burn/runway, capitalize-vs-expense routing, portfolio ROI), market-research (TAM/SAM/SOM top-down and bottoms-up, survey sampling with FPC, Kotler segmentation), and product-research (goal-matched study design, method-based saturation, insight synthesis flagging single-source anecdotes). Hard rules: outputs are estimates routed to a named clinical or finance owner, market sizes show method + assumptions, product insights require recurrence across independent participants. 24 stdlib Python tools, 12 reference docs. Distinct from ra-qm-team, finance, research/grants, product-team, and marketing-skill.
Persistent project planning files with lifecycle hooks that inject selected plan context. Automatic recovery uses project files only. Explicit catchup modes may read same-project local session records to emit aggregate counts or bounded nonce-framed excerpts. Optional gated mode can request continuation on capable hosts and never runs commands declared in Markdown. No network upload path. Installs across 60+ agents.
ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
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.
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.
Run a faster, provable month-end close. Three deterministic stdlib scripts: a close calendar planner that orders tasks by dependency, finds the critical path and slack, maps WD+n deadlines to dates and blocks on missing owners, missing or self-review of key controls and a critical path past the target workday; a reconciliation matcher that matches GL to bank or sub-ledger by reference then amount and date, builds the proof, ages reconciling items and blocks on any unexplained difference or preparer-as-reviewer; and a flux analyzer that applies your materiality rule and refuses material fluctuations explained with boilerplate or without a quantified driver. Ships cs-close-controller agent, /cs-month-end-close and /cs-flux-review commands, 3 references citing COSO 2013 and PCAOB AS 2201 / AS 2305 / SAPA 11, and a reconciliation sign-off template.
Development workflow skills, commands, and hooks
Build, evaluate, deploy, publish, and migrate Google ADK applications with Google's maintained agents-cli workflow for Agent Runtime, Cloud Run, GKE, and Gemini Enterprise.
Style-driven deliverable suite: slide decks (PowerPoint or HTML), multi-page HTML knowledge bases, and diagrams/data charts (Mermaid, SVG, or draw.io) that all render from one shared brand/style registry. Works out of the box with 5 built-in styles; add your own brand once and every deliverable matches. A librarian agent keeps sites and decks current: what's due, update plans, and scheduled fact-check sweeps.
Optimize hyperparameters using grid/random/bayesian search
Model interpretability and explainability
Проверка контрагента по ИНН: quick-scan по deal-killer-сигналам за минуты, полное досье по запросу, светофор 🟢/🟡/🔴 с рекомендацией «отсрочка / предоплата / избегать». Данные из реальных реестров, каждая цифра с источником и датой. | Counterparty risk check by INN over EGRUL/FSSP/courts/bankruptcy registries.
businessFuses OpenSpec (SDD) and Superpowers (TDD) into a complete Phase 0→4 workflow with multi-model progressive review, UltraReview gates, and convergence tracking. Use when starting any non-trivial development task.
developmentWarn-only, zero-dependency runtime harness layer for Claude Code (companion to superpowers): persistent state, scope control (prompt + action side), Default-FAIL verification & coverage gates, entropy governance (golden-rules + drift detection), and first-class C/C++ engineering (CMake/Meson/Make/Bazel + clang-tidy + sanitizers).
Design, generate, and run multi-agent AI pipelines — scope-aware, multi-pipeline, spec-driven, write/review-isolated, with step-level create/update/delete and integrated audit
developmentBatch-converts Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV and PDF to clean Markdown before the agent reads them — one file, a list, or a whole folder. Wrapper over firecrawl/anydoc with an honest OK/SKIP/ERROR summary and OCR routing for scans. | Пакетно конвертирует Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV и PDF в чистый Markdown до чтения агентом — один файл, список или целая папка.
productivity
