31 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 31 plugins that match these filters.
magnus-agent-skillsmagnus919/agent-skills2
thinking-skills-marketplacetjboudreaux/cc-thinking-skills1
gabbeandreibesleaga/GABBE1
anthropic-agent-skillsanthropics/skills1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplace28 eval-informed thinking skills for Claude Code, including first-principles, probabilistic reasoning, systems thinking, TRIZ, OODA, pre-mortem analysis, and more
GABBE ai skills (11): AI and agent engineering: multi-agent systems, agent UIs and protocols, context engineering, RAG evaluation, LLM-as-judge and reasoning patterns.
Appends two or three short follow-up questions after a substantive answer to help users check key facts, probe the reasoning, and notice missing context
vLLM operator reference suite — deployment, configuration, quantization, caching, KV, tool parsers, reasoning parsers, chat templates, benchmarking, performance tuning, observability, omni, input modalities, speculative decoding, NVIDIA hardware, and a Gemma 4 31B operating-point serve recipe.
inferenceAudits AI-assisted legal, compliance, governance, and institutional decisions before reliance to determine whether the responsible human or institution has enough access to the evidence, reasoning basis, uncertainty, authority, and review path to genuinely own the decision rather than merely approve, sign, or transmit it.
Audits legal AI outputs, prompts, skills, workflows and MCP/tool instructions for fluent but unsupported reasoning, missing evidence, overconfidence, hidden assumptions, weak causal links and absent human-review gates.
A drafting-and-review copilot for a founders' / co-founders' agreement — the terms fixing equity, vesting, IP, roles, control, deadlock, and departure between cofounders. Jurisdiction-agnostic, anchored on the Delaware C-corp default. Two modes: DRAFT (intake → equity & vesting → clauses → blocker triage → pre-signature check) and REVIEW (audit an existing agreement against an 18-clause checklist and red-flag scan). It handles the highest-dispute terms first-class: the equity split as documented reasoning (not a fake calculator), reverse vesting and the 83(b) clock, present-tense IP assignment (the Stanford v. Roche trap), leaver buyback and dead equity, and the deadlock clause most tools omit. It drafts for the venture, never one founder against another. Not legal advice.
Performs structured compliance review, clause redlining, and drafting suggestions for legal documents (privacy policies, data processing agreements, vendor and SaaS contracts) against India's DPDPA 2023 and the EU GDPR. Flags clauses as compliant, at-risk, or non-compliant with reasoning, and proposes ready-to-use model replacement language.
Assesses a legal argument, submission, or piece of structured reasoning from the perspective of a judge reading it cold under time pressure. Produces a structured seven-part assessment: what the case appears to be about, immediate points of confusion, what feels strong, what feels weak, what is assumed but unproved, a provisional confidence level (low/medium/high), and what would be needed to persuade. The skill does not rewrite, improve, or attack the argument — it tells you how it actually lands on a sceptical, experienced reader with no prior context. Works on skeleton arguments, witness statements, letters before action, position statements, academic articles, and non-legal structured reasoning.
Act as experienced opposing counsel to attack, undermine, and expose weaknesses in a legal argument, submission, witness statement, or structured reasoning. Produces a six-part adversarial analysis: 1. A core theory of attack identifying the single most effective way to defeat the argument; 2. A reconstructed version of the opposing argument stripped of rhetoric to expose its fragility; 3. Primary lines of attack grouped by category (legal misstatement, evidential gaps, causation failures, internal inconsistency, over-reliance on assertion, procedural weakness); 4. An "if I were the judge" section showing how a sceptical tribunal would dismantle the argument; 5. Surgical strikes - 3 to 5 high-impact points ready for oral submissions; and 6. An analysis of what the argument is trying to hide. Written in formal, adversarial British English for a legally trained audience.
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
88 curated skills (incl. workspace-mode for cross-repo flows), 30 composite slash commands, 14 specialist subagents with per-agent model + reasoning-effort tuning, and 10 hook scripts that quietly enforce discipline (confirm-to-commit on protected branches, destructive-git gating, no AI-attribution trailers in commits/PRs, dependency pre-flight, iron rules injected at session start). Covers the whole SDLC — including post-PR: CI diagnosis, releases, dependency audits, live incident response. Drives the senior-IC loop end-to-end via /orc:flow — workspace-aware: from a parent dir with multiple sibling repos, one flow spans them all with N linked PRs.
Research methodology and rigor scaffolds (Iron Laws, rationalization tables, decision flowcharts, systematic-reasoning checklists) (3 skills)
Public-safe preliminary screen for challenges to the impartiality of an AI evaluator, LLM-as-a-judge, decision-support agent, or adjudicative system based on prior outputs, suspected bias, unstable reasoning, or self-reinforcing memory. Use when asked whether an AI should be recused, disqualified, replaced, audited, or escalated. Does not decide real cases or claim that human judicial-recusal doctrine automatically applies.
Observability suite — metrics: Prometheus, Grafana Mimir, and Grafana reference for agents querying metrics, writing PromQL, building and fixing dashboards, and reasoning about SLOs, KPIs, and burn-rate alerting, plus the community, air-gapped mimir-distributed Helm upgrade methodology (chart↔app co-pinned ladder, the classic-vs-ingest-storage/Kafka decision, the nginx→gateway rename that silently moves the proxy's DNS name, rollout-operator sequencing and abort levers, per-hop verification, and air-gap image/CRD/egress staging); and logs: the kube-logging logging-operator (16-CRD Fluent Bit→fluentd/syslog-ng pipeline, JSON/CRI parsing, routing, buffers, upgrade floor 6.7.0) plus rancher-logging-exit — the air-gap-first migration off Rancher's frozen bundled rancher-logging chart (CVE-2026-54680, release-secret cutover, CR compatibility); and hardware metrics: snmp-exporter — Prometheus snmp_exporter v0.30.x best practices (generator.yml module curation, the never-walk-a-whole-enterpri
observabilityThe why layer of repo-native project memory: the reasoning behind a codebase, kept as Markdown in the repository.
Inference-API compatibility suite — the three open LLM serving protocols as third-party surfaces: OpenAI Chat Completions + legacy /v1/completions (7 local servers, gateways, 10 cloud compat endpoints, reasoning-field schism, client wire behavior), OpenAI Responses (spec, streaming events, store/previous_response_id semantics, translation), and Anthropic Messages (7 native server implementations, thinking-signature seam, stop_reason divergences, Claude Code/opencode integration). Source-examined at pinned commits with live-verification logs.
inferenceCreate, adapt, or revise Amazon-style narrative decision memos, six-pagers, PR/FAQs, and short decision briefs, including reading meetings and async review. Use for choosing the right memo form, evidence-led reasoning, and revising mechanical AI prose for human readers. Do not use for general copywriting, document rendering, or replacing incident reports and technical design records.
Build, test, sign, and ship mobile apps across iOS, Android, Flutter, and React Native — project scaffolding, builds and code signing, device and emulator testing, store submission (App Store and Play Store), app lifecycle and backgrounding, offline and sync, and mobile-specific testing. Use when the task involves creating, building, testing, or shipping a mobile app for iOS or Android, or reasoning about mobile behavior such as background execution, push notifications, offline storage, and data sync. Do not use for web frontend work (that is frontend-engineering), backend services and APIs (that is backend-engineering), or desktop and web platform targets outside the iOS and Android scope.
Make AI agent reasoning visible and auditable as an interactive graph. Arcgram turns walls of prose into typed nodes and explicit edges you inspect and correct node by node. Use it as a visual agent harness: propose → draw → self-audit → fix, human in the loop. Outputs one standalone HTML file: no build step, no npm, no CDN, no runtime. Ships authoring plus Checkpoint (diagram structure), Reconcile (diagram vs code), and Validate self-checks. Framework-agnostic and agent-neutral.
productivity
