54 Plugins aus öffentlichen Claude Code marketplaces. Jedes bündelt Skills, Slash-Commands, Agents, Hooks oder MCP servers, die zusammen installiert werden.
Zeige 54 Plugins, die diesen Filtern entsprechen.
rust-skillspo4yka/rust-skills3
claude-code-workflowswshobson/agents1
aiwgjmagly/aiwg1
trailofbitstrailofbits/skills1Reiche das repo mit .claude-plugin/marketplace.json ein und wir listen jedes plugin auf.
Marketplace einreichenSystems programming with Rust, Go, C, and C++ for performance-critical and low-level development
Take a side project from works-on-my-machine to a repo strangers install, trust and contribute to: a benefit-led README, a no-signup demo, an importer from competitors, good first issues, a licence audit and NOTICE file, fortnightly releases, one-command self-hosting, a read-only MCP server and the 20-second demo clip
Data & analytics skills: Metrics Framework, SQL Query Explainer, Dashboard Brief, Chart Data Extractor, Cohort Analysis, Data Pipeline Spec, A/B Test Readout, Metric Tree Builder, Data Quality Audit. Build metric trees, explain SQL, spec dashboards, run cohort retention with LTV modelling, design ETL/ELT pipelines, read out A/B tests with significance and guardrails, and audit datasets for quality before you trust them.
Applied security framework for cryptographic primitive selection, chain-of-trust design, authentication factor analysis, supply-chain trust, and physical-threat modeling. Complements OWASP-style application audits.
Compliance & trust skills for regulated and enterprise teams: SOC 2 Readiness, GDPR Compliance, HIPAA Safeguards, ISO 27001 ISMS, Vendor Security Review, and Data Retention Policy. Each ships a stdlib scoring/validation script.
Comprehensive Rust security code review with specialized bug-finding agents covering the safe/unsafe boundary, memory safety in unsafe blocks, concurrency, panic-induced DoS, recursion-induced stack overflow, FFI, and async runtime hazards
Add Arize AX observability to LLM applications — auto-instrumentation, trace export, dataset management, experiment workflows, prompt optimization, deep linking, and migrations from Langfuse, LangSmith, and Braintrust via the ax CLI.
Idiomatic development across C# /.NET, Go, Java/Kotlin, Python, Rust, TypeScript, shell, and web
Implement TypeScript, Python, Go, Rust, native apps, APIs and terminal workflows.
Rust, tokio, axum, serde, sqlx, and async concurrency code review
Reusable skills for AI coding agents. Every skill has a readable SKILL.md; 54 of 92 also carry a declarative protocol.yon with named steps, rules, and gates validated structurally by @younndai/yon-parser. Validation does not enforce runtime obedience. Read before you trust.
Post-hoc verification and trust audit of AI-generated factual and interpretive claims. Classifies claims by type and salience, routes them to domain-appropriate sources, scores trustworthiness on a tiered scale with an Interpolated verdict for plausible-but-unsupported detail, and assesses rhetorical fairness on interpretive claims. Designed with a focus on healthcare law in England and Wales, but with general applicability beyond.
Produces an adversarial attack on a legal argument that survives reply. Runs the opposing-counsel discipline twice: an unrestrained first pass, then the same instrument turned on that pass to cut every point that collapses under challenge - attacks on facts your own side has conceded, objections belonging to the wrong forum, speculation about documents and motives, gotchas with innocent explanations, overclaims, self-refuting assertions, and padding. The deliverable is one standalone attack containing only what can be defended, capped at five heads, not a discussion of the discarded draft. Use to attack, stress-test, red-team or rebut a submission, brief, motion, witness statement, letter or piece of structured legal reasoning when the output must be something you could stand up and say. Also use when an earlier adversarial review came back overlong, scattershot or padded with points you do not trust. Derived from Opposing Counsel Review by Larissa Meredith-Flister (Apache-2.0). Formal
Audit an AI agent skill before installing it. Use proactively whenever the user is about to add, install, enable, or evaluate an unfamiliar skill — including phrases like "audit this skill", "is this skill safe", "scan skill before install", "check skill for malicious code", "review this plugin", or any pre-install gate on an untrusted, third-party, or community-distributed skill bundle. Runs ten categories of static checks (code execution, network exfiltration, credential harvesting, persistence, prompt injection, supply-chain hooks, obfuscation, destructive filesystem ops, secrets, Trojan Source / homoglyphs) and emits a PASS / WARN / FAIL verdict.
All 51 Rust agent skills. The full listing overflows the skill listing of a 200K-context client; prefer one bundle, or add the AGENTS.snippet.md router.
Build, dependencies, and supply chain: 10 Rust agent skills.
White-box bug hunting, AI-agent and LLM red-teaming, cloud identity and CI/CD trust, client-app trust surfaces across browser and editor extensions and Electron, wire-protocol and token trust across gRPC, WebSocket, and JWT, enterprise identity lifecycle across SCIM and JIT provisioning, directory sync, MFA and key lifecycle, and Kerberos delegation, infrastructure-as-code and container hardening, mobile app security, smart-contract and DeFi review across EVM and Move, skill and MCP supply-chain vetting, API and object-authorization depth, host privilege escalation, network-service and transport trust, firmware and embedded-software trust, web trust boundaries, authentication and session depth, rate-limiting and multi-tenant isolation, injection and resource-exhaustion depth, file-upload and content handling, defensive detection and logging, supply-chain and dependency risk, business-logic and access-control depth, the classic web-attack classes across XSS, template and command injecti
securityFinds vetted agent skills for your task, mid-flow, from a federated catalog — with license/provenance trust metadata. Privacy-preserving: the search backend stays remote and only an abstract wish-list crosses the boundary.
Error discovery for AI products: read real traces, name failure modes and success modes by stage, and turn the ones that matter into code checks and AI judges you can trust. Includes Eval Studio and a zero-dependency command-line tool.
Language semantics and compiler errors: 8 Rust agent skills.
