Claude Skills by ruvnet

Create a new Architecture Decision Record with sequential numbering and AgentDB registration

Build or rebuild the ADR index + dependency graph by running scripts/import.mjs (handles v3-style and plugin-style ADR formats; one Bash call vs hundreds of MCP round-trips)

Review code changes against accepted ADRs for compliance violations

Read back adr-patterns + adr-edges namespaces, surface dangling refs / supersede cycles / status mismatches; exit 1 on cycles

Run an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtime

Create and manage sandboxed WASM agents for isolated code execution

Browse, publish, and install WASM agents from the community gallery

Query AgentDB through the controller bridge -- semantic routing, hierarchical recall, causal graphs, context synthesis, pattern store/search

Vector search via embeddings_* (large-scale HNSW) and ruvllm_hnsw_* (WASM router for ≤11 hot patterns), with RaBitQ 1-bit quantization for 32× memory reduction

Detect and flag personally identifiable information (PII) in text, code, and configurations

Scan inputs for prompt injection, unsafe content, and adversarial attacks using AIDefence

Run an autonomous /loop iteration -- check progress, work on next task, schedule next wake

Use learned patterns and current state to predict the optimal next action

Probe a site's authentication flow for redirect leaks, missing CSRF, weak session cookies, and OAuth misconfiguration; produces an auth findings.md

Extract structured data via stored browser-templates or one-shot DOM queries, with mandatory AIDefence PII + prompt-injection gates before content reaches the model

Fill a web form by mapping field-name → value, with optional template lookup from browser-templates for known forms

Drive an authentication flow once, sanitize cookies through AIDefence, and vault a reusable cookie handle in browser-cookies for future sessions

Open a named, traced browser session into an RVF cognitive container with a ruvector trajectory recording every action

Replay a recorded session trajectory against the same URL or a mutated variant; uses browser-selectors embedding similarity to recover from DOM drift

DEPRECATED in v0.2.0 -- use browser-extract instead; this is a thin shim for backward compatibility, removed in v0.3.0

Visual + DOM diff between two recorded sessions at matching trajectory step ids; used for visual regression and replay verification

UI test recipe -- composes browser-record (capture) + browser-replay (verify) so every test produces a replayable RVF artifact, not an ephemeral run

Discover and recommend ruflo plugins based on your workflow, installed MCP tools, and current task

Initialize a new Ruflo project with MCP tools, hooks, and agent configuration

Run health checks on the Ruflo installation and fix common issues

Sign, verify, and track fix-marker regressions over time using a deterministic Ed25519 witness manifest. Works in any project — clone the toolkit, run init, register fixes, regen on each release.

Run the corpus benchmark — booster locally, optional Gemini/Sonnet/Opus baselines — and persist a verifiable measured-vs-claimed table

Apply a simple code transform via agent-booster's WASM engine — sub-millisecond, deterministic, $0 (no LLM call). Companion to cost-booster-route.

Route tasks through hooks_route, partition by Agent Booster availability, and report Tier 1 bypass utilization with $0 cost

Read accumulated cost-tracking spend + budget config, compute utilization, emit 50/75/90/100% alert ladder

Wrap getTokenOptimizer().getCompactContext() to retrieve compacted ReasoningBank context for cost-analysis queries; report bridge-reported tokensSaved

Per-conversation cost view — list every session in cost-tracking with started-at, message count, top model, and total cost

Export cost-tracking telemetry in Prometheus textfile or webhook JSON formats — for external observability (Grafana, Datadog, custom dashboards)

Consumer-side wiring for ADR-097 Phase 3 federation_spend events — per-peer rolling windows + suspension-threshold check

Analyze token usage patterns and recommend cost optimizations with estimated savings

Generate a cost report showing token usage and USD costs by agent and model

Single-shot programmatic dump of all cost data — total spend, per-tier, top session, budget status, federation aggregate. JSON or markdown.

Auto-capture per-session token usage from the Claude Code session jsonl and persist to the cost-tracking namespace

Read every docs/benchmarks/runs/*.json and surface drift in win rate, latency, escalation rate, and LLM-baseline cost over time

Define and manage cognitive patterns for agent reasoning and decision-making

Create and adapt Dynamic Agentic Architecture agents that learn and evolve

Scaffold an aggregate root with entity, value objects, repository interface, domain events, and test stubs

Create and manage a DDD bounded context with standard directory structure

Validate domain boundaries -- detect cross-context import violations and aggregate invariant issues

Generate API documentation from source code with JSDoc and OpenAPI support

Generate and maintain documentation with drift detection

Query federation audit logs with compliance filtering

Initialize federation on this node — generate keypair and configure peers

Show federation health — peers, sessions, trust levels, and message metrics

Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings