23 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 23 plugins that match these filters.
wasp-nestlegioncodeinc/vibe-coding-tools2
magnus-agent-skillsmagnus919/agent-skills2
cursor-rules-javajabrena/plinth2
claude-code-skillsalirezarezvani/claude-skills1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplaceRoll Claude Code out to a team with guardrails you can check. Four deterministic stdlib scripts: a settings linter that reads shared, local, user and managed settings together (array merge, deny-ask-allow order) and blocks blanket shell allows, pre-approved destructive commands and committed credentials; an MCP and plugin inventory that blocks anything missing from your approved list or holding a literal secret, and flags unpinned or plain-http servers; a CLAUDE.md layering audit that resolves every layer and @import and flags broken imports, contradictions, secrets and resident size; and a privacy-safe adoption tracker that turns local session files into counts only and classifies the rollout as PILOT, SPREADING, EMBEDDED or STALLED. Ships cs-claude-code-rollout agent, /cs-claude-rollout and /cs-claude-settings-lint commands, 3 references, a baseline managed-settings policy and a four-phase rollout plan.
Compose repository baseline, safe refactoring and contributor onboarding through selected specialist owners.
Test data engineering: Faker and factories, WireMock and MSW API mocks, seed datasets, golden files, and boundary, pairwise and negative test inputs. Includes FactoryBot, Mimesis and Bogus, a Mountebank reference, synthetic PII, and a malicious payload bank. Agents (golden-file-manager, test-data-setup-agent) maintain snapshot baselines and set up a feature's full test-data layer.
foundationsDrafts a customized SaaS Customer Agreement starting from the Y Combinator standard form SaaS template. Runs a structured intake covering fee structure, data handling, ML/AI rights, implementation services, SLA, and governing law, then applies 18 always-on professional defaults plus 12 conditional decisions. Outputs a clean .docx ready for review alongside a lawyer-facing memo that itemizes every change from the YC baseline and flags each item still requiring attorney input. Aimed at startup founders preparing first-draft customer subscription agreements.
Matter scoping across the full pre-execution arc — organise client data into a structured brief, capture the agreed baseline, or reconstruct scope mid-flight. Use when making sense of client information before a proposal, scoping a new matter, running a kickoff, defining scope, mapping stakeholders, or inheriting a matter mid-flight.
Scope management for legal matters — baseline capture, in-flight change control, OOS documentation, and scope retrospective. Use when asked to review scoping assumptions, assess whether work is in or out of scope, draft a scope change notice, track scope changes, prepare an OOS justification, run an OOS report, prepare a scope call agenda, or review what changed on a matter.
The full cap-evolve skill library: intake, implement-and-check, evaluate, diagnose, gate, baseline, finalize, report; capability/algorithm/optimizer skills; and an autonomous orchestrate skill.
Visual regression testing with Percy, Chromatic, Playwright screenshots and Storybook, plus chart rendering tests for Chart.js, D3 and Vega. Covers responsive breakpoint matrices, baseline conventions, and a binding baseline gate. Agents (visual-diff-classifier, visual-baseline-curator) sort diffs into intentional, incidental or regression and propose an initial baseline set.
quality-engineeringExpert guidance for FedRAMP certification and compliance under CR26 (FedRAMP Consolidated Rules for 2026). Use this skill whenever a user asks about FedRAMP authorization, ATO (Authority to Operate), cloud security for federal government, NIST SP 800-53 controls, CSP compliance, or any of the core FedRAMP document types: SSP, SAP, SAR, POA&M, CIS/CRM workbooks. Also trigger for questions about FedRAMP Certification Classes (A, B, C, D — new baseline labels: A = pilot/transitional, B = LI-SaaS/Low, C = Moderate, D = High, per NTC-0004), FedRAMP 20x (now the primary authorization pathway), OSCAL mandate (September 2026), 3PAO assessments, continuous monitoring (ConMon), gap assessments, system boundary definition, or architecture reviews for federal cloud. FedRAMP Ready retires July 28, 2026. When in doubt, use this skill — it covers the full FedRAMP lifecycle from readiness through continuous monitoring.
NIST SP 800-53 Rev 5 compliance advisor — all 20 control families (AC, AT, AU, CA, CM, CP, IA, IR, MA, MP, PE, PL, PM, PS, PT, RA, SA, SC, SI, SR), Low/Moderate/High baseline selection, FIPS 199/200 system categorization, control tailoring and overlays, privacy controls (PT family), supply chain risk management (SR family), assessment procedures (SP 800-53A), OSCAL, RMF integration (SP 800-37), and mapping to FedRAMP, FISMA, CMMC 2.0, and ISO 27001. Use for any federal system security controls, FISMA compliance, RMF step guidance, control narrative writing, or baseline tailoring question.
Jurisdiction-aware banking regulatory agent: 16 product skills, 7 jurisdiction overlays, 4 domain commands. IFRS 9 ECL, Basel III/IV capital and liquidity, AML/KYC/sanctions, bank reconciliation across UK, EU, US, Australia, Singapore, UAE, Pakistan.
financePrepare an app library, contracts, schema baseline and a wave handoff before building.
Design and establish Volcengine landing zones, organizations, identity, account factories, and governance baselines.
identity-and-access-controlVisual regression testing — screenshot baselines, determinism, diff review, baseline custody and CI wiring. Load when adding, reviewing or debugging tests that compare a rendered subject against an approved image.
Plan and execute production ML engineering work — classifier versus generative model selection, zero-shot baselines, coding specialization, model training and fine-tuning (LoRA/QLoRA), evaluation and eval-set design, quantization decisions, inference deployment, lineage, feature parity, drift response, and regression triage, experimental weight inspection and targeted editing, grounded in practical engineering patterns for production ML systems. Do not use for statistical modeling and experimental design (that's the data scientist) or for operating a specific inference engine (that's a tool skill such as llama-cpp or vllm).
Optimize software performance through user-journey baselines, profiling, representative benchmarks, controlled experiments, and field verification. Use when asked to make an application, service, workflow, or hot path faster or more efficient, or to build the measurement loop first. Do not use for a reliability incident, capacity forecast, generic product A/B test, or operating a named telemetry or load-testing tool without an optimization objective.
Shift-right production QA: synthetic monitors, canary validation against baseline metrics, and release runbooks. Follows the ISTQB definition of shift right (testing a system continuously in production) and covers RUM coverage gaps and multi-team cutovers. An agent (observability-to-test) turns production alerts and errors into regression tests.
operations-resilienceUse when you need to verify Java performance optimizations by comparing profiling results before and after refactoring — including baseline validation, post-refactoring report generation, quantitative before/after metrics comparison, side-by-side flamegraph analysis, regression detection, or creating profiling-comparison-analysis and profiling-final-results documentation.
Use when you need to add or review Flyway database migrations in a Spring Boot application — Maven dependencies, db/migration scripts, spring.flyway.* configuration, baseline and validation, and alignment with JDBC or Spring Data JDBC.
Map any Instagram Reels niche end to end with Apify Actors, then turn what works into hooks for your own content. Finds the reels that already won (Popular search + hashtags), shortlists creators who reach people consistently (median plays, topic share, activity), separates real outliers from weak baselines (lift vs the creator's own median, share rate), transcribes only the winners, groups their hooks into patterns, and rewrites the user's own reel idea, script or caption with those patterns. Use when the user asks to research a niche on Instagram, find the best creators or influencers in a topic, see which reels perform, find outlier or viral reels, study hooks, get hook ideas, or improve a reel hook using what works in their niche — even if they don't say "niche map". Also for weekly re-runs of an earlier map.
