claude

trust-and-safety

Trust & Safety team — agents for content-moderation and abuse-detection work. The trust-safety-policy-lead designs the policy taxonomy + enforcement ladder, the human-review operations layer (queue prioritization, reviewer wellness, escalation, appeals/due-process), and the measurement frame (prevalence, enforcement precision/recall, time-to-action SLA, appeal-overturn rate). The abuse-detection-engineer builds the detection stack: signals, rules-vs-ML classifiers, reviewer queues, thresholds tied to precision/recall. skills, a knowledge bank (a Mermaid enforcement decision tree + a T&S metrics catalogue with formulas), templates, best-practice rules, and an advisory hook. Seams: classifier-eval validity → applied-statistics; PII → data-governance-privacy; account-takeover → security-engineering; LLM-classifier build → claude-app-engineering. Enforcement is proportional; appeals are due process; measure prevalence, not just volume. Requires ravenclaude-core@>=0.7.0.

9 on GitHubby Matt Corbettv0.1.2MITupdated today
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Plugin trust-and-safety from marketplace ravenclaude in mcorbett51090/RavenClaude. Commands read from the repo's manifest — today.

This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.

What it installs

Skills (3)

  • build-abuse-detection-pipeline

    Design an abuse/fraud/spam detection pipeline — inventory signals, decide rules vs. ML (or hybrid), wire signal → score → threshold → action/reviewer-queue, and set the operating point from a precision/recall tradeoff. Reach for this when the user asks to catch an abuse type, choose signals, or rout

  • design-moderation-policy

    Design a content-moderation policy from scratch — a policy taxonomy (categories + severity tiers), a proportional enforcement ladder (warn / limit / remove / ban), and a real appeal path — by traversing the enforcement decision tree. Reach for this when the user asks to design or review a moderation

  • measure-enforcement-quality

    Build the Trust & Safety measurement frame — prevalence (not just volume), enforcement precision/recall, time-to-action SLA, and appeal-overturn rate — with the formulas and the applied-statistics seam for eval validity. Reach for this when the user asks what to measure, whether moderation is workin

Subagents (2)

  • abuse-detection-engineer

    Use to build the abuse/fraud/spam detection stack — 'what signals?', 'rules or an ML classifier?', 'where to set the threshold?', 'how to route to a reviewer queue?', 'precision vs recall?'. Signals before models; every threshold tied to precision/recall. NOT policy/appeals design (policy-lead).

  • trust-safety-policy-lead

    Use for Trust & Safety policy + operations — 'design a moderation policy', 'what enforcement ladder?', 'how to prioritize the review queue?', 'is our appeals process fair?', 'what T&S metrics?'. Proportional enforcement; appeals are due process; measure prevalence. NOT detector-build (abuse-eng).

Hooks (1)

  • PreToolUse

    /usr/bin/env -u BASH_ENV -u ENV -u SHELLOPTS -u BASHOPTS -u LD_PRELOAD -u LD_LIBRARY_PATH -u LD_AUDIT -u DYLD_INSERT_LIBRARIES -u DYLD_LIBRARY_PATH -u PYTHONPATH -u PYTHONSTARTUP PATH=/usr/local/bin:/

View source on GitHub mcorbett51090.github.io

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Power Platform specialist team — agents (incl. power-platform-tester, power-bi-engineer) and skills, with strong ALM/git coverage for solutions, flows, and PBIP. A house-opinions hook flags 8 §3/§4 violations; the knowledge bank carries production decision trees (PA-flow recovery, Dataverse token-acquisition, PCF React surface, PBI deploy/refresh, custom-connector build-path, PBIR Enhanced infinite-spinner debug + full build reference, DAX silent-zero scoring via the `Domain` pattern, sempy.fabric notebook reference, Power BI Copilot report-readiness, Code Apps connector gotchas, PBIP deployment variables + #839, PBIR reference enrichment, PBIP report fast-solve triage router [MCP-optional], main-forms-are-Web-API-authorable grounding) plus a real-engagement scenarios bank. Bundles the community pbix-mcp server (d0nk3yhm/pbix-mcp, MIT) for .pbix/.pbit read/write/DAX-eval (`pip install pbix-mcp`); documents (not bundles) the official Microsoft Dataverse MCP (CLAUDE.md §9a). Extends ravenclaude-core.

24 skills · 8 commands · 11 agents · 1 MCP server · hooks

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finance

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Corporate finance & FP&A specialist team — FP&A analyst (budgets, forecasts, variance commentary), financial modeler (3-statement, DCF, scenarios), controller (close, JEs, reconciliations), treasury analyst (cash, covenants, FX), valuation analyst (DCF + comps + precedent), audit-prep specialist (PBC, walkthroughs, SOC1/2 narratives), and board-pack composer. skills incl. a gold-standard NetSuite close (OAuth2 M2M + SuiteQL BS/IS trial balance, layperson runbook), templates, a knowledge bank (ASC 805 / 718 / 740, accrual-cutoff, WACC, cost accounting, FP&A operating model + decision support, NetSuite integration landscape), advisory hooks (hardcoded rates / plaintext PII / missing Sources / Assumptions; secrets-PII scan). Inherits ravenclaude-core protocols.

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web-design

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Web design & build specialist team — web architect (IA, stack, hosting), UX designer (wireframes, flows, conversion), visual designer (brand, typography, tokens), frontend implementer (HTML/CSS/JS, React, Astro, Next), content strategist (copy, microcopy, SEO content), accessibility auditor (WCAG 2.2 AA/AAA), and performance engineer (Core Web Vitals, image/font optimization). skills (the gold-standard-website-pipeline gated build pipeline, static-site build, design-system audit, card/tile UI, accessibility review, Core Web Vitals tuning, technical SEO audit, information architecture, conversion design, content audit, design-tokens scaffolding, third-party hygiene, Fluent UI v9 + React implementation), templates, an advisory hook, and a knowledge bank seeded with a curated 2026 reference set of "cutting edge yet simple" marketing-site donors — the design agents carry compact inline priors plus a pointer to the full brief. Inherits ravenclaude-core protocols.

19 skills · 7 commands · 7 agents · hooks · LSP

9

edtech-partner-success

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EdTech-flavored Partner Success Manager team — specialist agents anchored on the PSM lane, with skills, templates, an advisory hook, a knowledge bank with Mermaid decision trees, a engagement bank, and a stdlib psm_calc.py calculator (seat-utilization / renewal-NRR-forecast / time-to-value). Covers QBRs, success plans, health scores, a self-contained Power-BI-style partner-health report, onboarding, touchpoint logs, adoption sequencing, 90-day implementation arcs, train-the-trainer curricula, advocacy/reference pipelines, renewal decision memos, and the integration contract for a centralized CS dashboard (Planhat + Salesforce + Snowflake + Zapier + Granola). Team growth ships as skills + knowledge + templates, not parallel agents. Primary-source citations with retrieval dates. Vertical-explicit but segment-agnostic — fits K-12, higher-ed, corporate L&D, or mixed EdTech books. Inherits ravenclaude-core protocols including the alternate-methods Capability Grounding Protocol.

17 skills · 5 commands · 6 agents · hooks

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regulatory-compliance

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Financial-regulatory & compliance specialist team — function agents (AML/KYC, regulatory-reporting, risk-and-controls, policy & procedure, examination-prep, Bermuda-insurance) PLUS jurisdiction/regulator specialists: BMA financial-institutions (banking, trust, corporate-services, fund-admin, investment-business, money-service, digital-assets — the primary build-out, with deep AML/ATF + supervision/fees + licensing-classification trees), CIMA (Cayman), Bahamas, Channel Islands (Jersey JFSC + Guernsey GFSC), UK PRA, and US federal+state. primary-source-cited regulator knowledge files, best-practice rules, skills, templates, a defensive PreToolUse hook (PII scrub — SSN/IBAN/credit-card/Bermuda TIN/wire instructions). Positioning reflects field experience inside a Tier-1 financial regulator (BMA). Inherits ravenclaude-core protocols.

11 skills · 5 commands · 12 agents · hooks

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