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Found 1,462 Skills
Run bounded, evidence-driven training research through W&B Launch: assess project readiness, establish launchable code and queue capacity, smoke-test real jobs, execute serial trials, compare metrics, and persist resumable research state. Use when a coding agent is asked to autonomously test training hypotheses or tune a real W&B-tracked workload.
Score text from -1 (strongly negative) to +1 (strongly positive) with a label, handling negation, intensifiers and emphasis. Called as POST /v1/text/sentiment, it takes text and returns score, label, matches, positiveTerms. A support-triage or review-monitoring agent must decide whether a message is a complaint before it routes or escalates it, and a model call for one number costs more than this and is not reproducible. Reading this schema and dry-running the call are free and need no wallet; a real call costs $0.004, paid in USDC on Base over x402.
All-in-one skill for CLAUDE.md files. Two modes: `audit` finds drift (claimed facts no longer matching code), leaked secrets, duplicates, instruction-budget bloat, and prescriptive-vs-descriptive imbalance across all CLAUDE.md files in your projects. `improve` measures one CLAUDE.md against Anthropic's official best practices (200-line budget, removability test, emphasis tuning, 3-tier hierarchy) plus community-validated guidance, then proposes concrete rewrite diffs applied only after user approval. Default behavior auto-detects: in a project with a CLAUDE.md → improve mode; otherwise → audit all. Use when: 'audit claude.md', 'check claude md drift', 'lint CLAUDE.md', 'claude md audit', 'refresh instructions', 'improve CLAUDE.md', 'restructure CLAUDE.md', 'tune CLAUDE.md', 'apply CLAUDE.md best practices', 'is my CLAUDE.md good', 'CLAUDE.md is too long', 'rebalance CLAUDE.md', or quarterly as a hygiene check.
Use the free You.com MCP profile for unauthenticated basic web search with `you-search` only.
Periodic evidence-based self-audit of the whole agent system — the orchestrator, its docs/SSOTs, rules, memory, subagents, tools, infra and the work it claims to have delivered — followed by immediate cheap-safe fixes and a ranked backlog. Use when the user says 'аудит системы', 'проверь себя', 'самопроверка', 'system audit', 'audit yourself', 'health check', 'что у нас накопилось', 'система раздулась', 'проверь что работает а что на бумаге', 'gap-анализ', 'что удалить', or on cadence triggers (every ~10 sessions, before a milestone, after a big refactor, when memory hits its caps, when onboarding this repo to a new agent). Seven lenses: delivery reality · knowledge drift · operational layer · layer telemetry (did it ever fire) · tools & infra · domain gaps · anti-bloat subtraction. Not for reviewing a single diff (use a diff-review pass) and not for probing a running product (use /memory-kit:qa-sweep).
Preview, submit, inspect, and manage Alpaca paper-trading orders across US equities, options, and crypto. Use this skill when you want your AI agent to take a strategy signal — from a backtest, manual idea, or automated system — and execute it safely in your Alpaca paper-trading environment. This generic version works with any Alpaca SDK, REST API call, or agent tool that can reach the Trading API.
A brief description of what this skill does
Use this skill to set up and configure the Education Cloud Student Recruitment Agent (SRA) — the packaged Agentforce agent (namespace sturecruitment) that answers admissions FAQs, captures inquiries, registers campus tours, and files applications for prospective students. TRIGGER when the user wants to: create or configure an admissions, recruitment, or enrollment agent, set up the Student Recruitment Agent, deploy SRA to an Experience Cloud site, clone the SRA flows or permission sets, add the SRA subagents (Admissions and Enrollments FAQ; Admissions Application; Campus Tours, Visits, and Events Registration; Request for Information), wire Learning Program grounding, or build the escalation subagent. Guides platform enablement, permissions, grounding, agent creation, and channel deployment — API-first with UI fallback. DO NOT TRIGGER for the Transfer Credit Agent, generic Agentforce authoring (use agentforce-generate), or base Education Cloud domain enablement.
Evaluate Python AI/agent code against a dataset of test cases using pydantic_evals, and review results in Logfire's Datasets & Experiments UI. Also covers redirecting an existing Braintrust Eval() suite to Logfire with no code changes. Use this skill whenever the user asks to "set up evals", "add an evaluation", "test my agent against cases", "write a dataset of test cases", "score my LLM output", "add an LLM judge", "check tool-call correctness", "send Braintrust evals to Logfire", "migrate from Braintrust", or mentions pydantic_evals, Braintrust, Datasets & Experiments, or evaluating AI/agent behavior against known inputs. The `pydantic_evals` workflow is Python-only; the Braintrust redirect also supports TypeScript suites, env-vars-only. Both are for scoring DEFINED test cases offline — not for instrumenting live production traffic (use `logfire-instrumentation` for that) and not for infrastructure monitoring (use `logfire-infrastructure`).
Connect @real-a11y-dev/mcp to Cursor, Claude Code, Claude Desktop, VS Code, or other MCP clients. Use when adding Real A11y MCP, configuring npx @real-a11y-dev/mcp, setting storage-state / CDP / ALLOWED_ORIGINS, or smoking audit_page from an agent.
Distribute a skill across the 4 agent skill folders (Codex, Claude Code, Pi, Hermes) so all agents see it. Use when the user says "distribute this skill", "sync skills across agents", or after creating/updating a skill that should be global. Covers the symlink layout and the ~/.pi/agent/skills trap.
Deep-scrape a person across X, LinkedIn, GitHub, and the open web to judge if they are legit. Manual-only; invoke with /who-is-this. Use when the user says who-is-this, "who is this", "who is this guy", "research this person", "are they legit", "vet this founder", or drops a profile screenshot. Differentiator vs twitter-alpha: one-person background check, not a 7-person idea list. Differentiator vs deep-research: platform scrapes plus a short verdict, not a long cited memo.