Agent Skills

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name: check

description: Run the scored pre-publish gate via eval-runner.py: claims, brand voice, compliance, AI tells. "check this before we publish"

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name: churn-risk

description: Score churn risk per segment by script, with tiered retention playbooks. "which customers are about to churn"

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name: claude-authenticity

description: Detect whether an API endpoint is backed by genuine Claude (not a wrapper, proxy, or impersonator) using 9 weighted rule-based checks that mirror the claude-verify project. Also extracts injected system prompts from providers that override Claude's identity. Fully self-contained — copy the code below and run, no extra packages beyond httpx. Use when the user wants to verify a Claude API key or endpoint, check if a third-party Claude service is authentic, audit API providers for Claude authenticity, test multiple models in parallel, or discover what system prompt a provider has injected.

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name: client-onboarding

description: Build a client onboarding pack: kickoff agenda, discovery questions, 30-60-90. "we just signed a new client"

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name: client-proposal

description: Draft a client proposal or RFP response: scope, deliverables, KPIs, pricing tiers. "respond to this RFP"

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name: client-report

description: Write a white-labeled report for one client from tracked data. All clients → agency-dashboard. "prepare the monthly client report"

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name: client-validation-document

description: Produce the Part 5 client validation document: evidence-cited findings for client decisions. "prepare v1 findings for client review"

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name: eval-design

description: Use when the user needs to design evaluation datasets, create test cases, stratify samples, generate adversarial examples, extract eval dimensions from traces/specs, or build a labeled evaluation set. Also use when the user mentions test data design, eval coverage, difficulty stratification, synthetic data generation for eval, or "how to create good evaluation data." Outputs datasets in OpenJudge-compatible format.

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name: eval-report

description: Use when the user has run multiple evaluation skills and wants a comprehensive analysis — maturity assessment, cross-skill signals, trends, prioritized actions, and an executive summary. Also use when the user mentions eval health check, evaluation audit, ship readiness, evaluation maturity, or "how good is my evaluation system itself." This is a read-only analysis skill.

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name: find-skills-combo

description: Discover and recommend **combinations** of agent skills to complete complex, multi-faceted tasks. Provides two recommendation strategies — **Maximum Quality** (best skill per subtask) and **Minimum Dependencies** (fewest installs). Use this skill whenever the user wants to find skills, asks "how do I do X", "find a skill for X", or describes a task that likely requires multiple capabilities working together. Also use when the user mentions composing workflows, building pipelines, or needs help across several domains at once — even if they only say "find me a skill". This skill supersedes simple single-skill search by decomposing the task into subtasks and assembling an optimal skill portfolio.

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name: meta-eval

description: Use when the user wants to build an evaluation system for an LLM/agent application but doesn't know where to start — they have traces, prompts, RAG pipelines, or nothing at all. Also use when the user mentions evaluation, eval, benchmarking, testing LLM quality, measuring agent performance, assessing RAG accuracy, or wants to compare prompts/models. This skill is the entry router: it asks diagnostic questions then recommends which sub-skill (local workflow) to use next.

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name: metric-design

description: Use when the user has evaluation principles or a dataset but needs help choosing the right graders, designing evaluation metrics, creating LLM-as-judge prompts, combining multiple metrics into a composite score, or building an automated evaluation pipeline. Also use when the user mentions grader selection, metric design, judge prompt engineering, rubric design, evaluation pipeline code, or "how to evaluate [X] automatically." Outputs executable OpenJudge pipeline code.

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name: mmx-cli

description: Generate text, images, video, speech, and music via the MiniMax AI platform. Covers text generation (MiniMax-M3 model), image generation (image-01), video generation (Hailuo-2.3), speech synthesis (speech-2.8-hd, 300+ voices), music generation (music-2.6 with lyrics, cover, and instrumental), and web search. Use when the user needs to create AI-generated multimedia content, produce narrated audio from text, compose music, or search the web through MiniMax AI services.

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name: prompt-regression

description: Use when the user has changed a prompt (system prompt, RAG template, agent instruction, etc.) and wants to know whether the candidate is better or worse than the baseline. Also use when the user mentions prompt A/B testing, prompt comparison, prompt optimization validation, "did my prompt change help," or prompt regression testing. Outputs per-dimension win rates with statistical significance using OpenJudge PairwiseAnalyzer.

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name: rag-eval

description: Use when the user has a RAG (Retrieval-Augmented Generation) system and wants to evaluate its quality — separating retrieval issues from generation issues. Also use when the user mentions RAG evaluation, faithfulness checking, hallucination detection in RAG, retrieval quality, chunking optimization, or "is my RAG pipeline working." Outputs a diagnostic matrix that pinpoints whether problems are in retrieval or generation.

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name: redteam

description: Use when the user wants to test their LLM/agent application for safety and security vulnerabilities — jailbreaks, prompt injection, PII extraction, harmful content generation, or evaluator gaming. Also use when the user mentions security testing, adversarial testing, red teaming, safety evaluation, ASR (Attack Success Rate), or "is my app safe to deploy." Outputs ASR paired with over-refusal rate and an audit document.

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name: agent-authority-charter-builder-arkadiy-miteiko

description: Creates an Agent Authority Charter for enterprise or regulated AI agents before deployment. Use this Skill when a user needs to define what an AI agent is allowed to do, who delegated authority to it, what actions are permitted or prohibited, when human approval is required, what evidence must be preserved, and how the agent can be suspended, revoked, or escalated.

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name: ai-audit-trail-larissa-meredith-flister

description: This skill builds a structured audit trail of an AI-assisted task: what the tool was asked to do, what materials it was given, what it produced, how the output was verified, and what was ultimately relied upon. It documents the workflow for supervision and later review without ruling on privilege or disclosure, so the record stays accurate rather than self-serving.

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name: ai-governance-reviewer-carl-ditzler

description: Use this skill when the user wants an AI governance, legal-risk, privacy, compliance, procurement, or vendor-risk review of an internal AI use case, an AI product feature, an LLM workflow, or a third-party AI vendor. The skill asks intake and clarifying questions first when facts or evidence are missing, identifies required documentation and missing evidence, maps the use case to AI governance frameworks and applicable legal domains, and produces a preliminary or final governance review with scorecards, findings, owners, remediation actions, and follow-up questions.

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name: ambiguity-report

description: Turn an interpretive-ambiguity audit of a legal text — contract, statute, regulation, or judicial opinion — into a polished deliverable. Produces a multi-page website (default), a single-page interactive site, a Microsoft Word document, a PowerPoint deck, or a LaTeX/PDF. Use whenever a user has a stress-test result, ambiguity audit, or "where will this be litigated" scenarios and wants to publish, present, or share them. Triggers on "publish the audit," "make a report from this," "turn this into a website / deck / brief / Word doc," "make a Netlify site," "build slides of these ambiguities," "render the scenarios," "package this stress test," "produce a LaTeX version," and similar. Pairs with the ambiguity-stress-test skill (the underlying analysis) but works on any structured or semi-structured ambiguity analysis. Visual design is opinionated but the user can override colors, fonts, and brand label. Most formats need Python and a writable filesystem; single-file HTML works where the host has neither.

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name: ambiguity-stress-test

description: Adversarially stress-tests a legal text — a contract, statute, regulation, or judicial opinion — for interpretive ambiguity: it finds the seams where the people governed by it will later disagree about what it means and turns each into a concrete dispute scenario with both sides' arguments, the likely outcome, and a fix. Use it whenever someone wants to pressure-test, red-team, audit, or find weak spots, loopholes, gaps, ambiguities, or drafting problems in a legal document; whenever a drafter wants to tighten a contract, statute, regulation, or opinion before it issues; whenever a litigator wants to mine an opinion or contract for arguments; or whenever someone hands over a legal text and asks where it will be fought over or for issue-spotting. Trigger it for contract review, statutory-ambiguity analysis, judicial-opinion scope analysis, and drafting QA — even if the user never says "stress-test" or "ambiguity."

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name: analyse-dpa-fournisseur-hugo-salard

description: Analyse systématique d'un Data Processing Agreement (DPA) au regard de l'article 28 RGPD, des lignes directrices EDPB 07/2020 et 02/2024, des CCT 2021 (décision d'exécution 2021/914), des recommandations EDPB 01/2020 (mesures supplémentaires post-Schrems II), et du Règlement (UE) 2024/1689 (Règlement IA). Produit un rapport structuré clause par clause (18 clauses : 13 obligatoires + 5 complémentaires) avec diagnostic 🟢/🟡/🔴, remédiations prêtes à insérer, analyse détaillée des transferts internationaux, vérification Règlement IA, et questions à poser au fournisseur. Triggers : "analyse de DPA", "audit DPA", "vérifier un DPA", "DPA fournisseur", "data processing agreement", "art. 28 RGPD", "sous-traitant RGPD", "négociation DPA", "review DPA", "conformité contrat sous-traitance".

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name: arbitration-clause-design-and-review-hafez-virjee

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name: archeologue-gallica

description: Archéologie des sources juridiques anciennes via Gallica (BNF, API stables, sans clé) : débats parlementaires du JO depuis 1871 (genèse des lois de la IIIe République), notes d'arrêt et doctrine d'origine dans les recueils Sirey et Dalloz, Bulletins civil et criminel anciens, Recueil Lebon, JO Lois et décrets 1881-2015, thèses et traités du XIXe-début XXe, Gazette des tribunaux, Bulletin de l'Inspection du travail. Déclencher dès que l'utilisateur cherche l'origine historique d'un texte, d'un concept ou d'une jurisprudence : « débats de la loi de 1884 », « note de Josserand », « que disait la doctrine en 1900 », « première apparition de la notion de… », « généalogie / histoire de l'article… », « arrêt ancien », « thèse d'avant-guerre », « Gallica », « BNF », ou toute recherche juridique antérieure aux bases modernes (Légifrance ne remonte pas avant l'époque contemporaine, Judilibre non plus). Déclencher aussi en COMPLÉMENT de travaux-preparatoires quand la loi étudiée est antérieure à 1958.