「raft」の検索結果

Use when you need to know where a piece of reporting actually came from — the user gives an article URL and asks "where does this come from?", "who is the original source?", "is this just a rewrite?", or another skill needs the provenance chain before grading or citing a report. Follows an article's links and named attributions back to the originating vendor, government, victim or actor document and returns the chain, the primary's stated access and confidence language, publication dates, and every hop it could not resolve. Deterministic — a script or the Liberty91 platform resolves the chain; the model does not reconstruct it from memory. Invoked by /quality-of-information-check, /threat-actor-profiling, /campaign-tracking and /intelligence-writing. Works on any URL with no API key.

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Use when the user asks "what TLP should this be?", applying TLP markings to a finished product, or the tradecraft pipeline calls for TLP determination before sharing. Covers TLP v2.0 (CLEAR / GREEN / AMBER / AMBER+STRICT / RED).

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Indicator pivoting methodology — how to use one known indicator to discover related infrastructure across the IOC graph. Decision tree by indicator type with concrete `/lookup-*` commands per pivot, a worked multi-hop example, pivot-quality scoring, and routing into the rigor pipeline. Use when the user asks "what else is connected to this IP / domain / hash / cert / actor?", needs to expand a single seed IOC into a campaign cluster, or wants the canonical reference for graph-walking IOCs.

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Use when a report or article needs to be split into individual claims before it is graded, cited or used as evidence — the user asks "what does this report actually claim?", "split this into claims", "separate the facts from the judgements", or another skill needs a claim list. Turns one document into five to twelve atomic claims, each typed (observation, attribution, assessment, actor claim, victim disclosure) and anchored to the verbatim sentence it rests on, so every extraction can be checked against the source. Preserves the source's own hedging. Does not grade. Invoked by /quality-of-information-check; its output feeds /ach, /key-assumptions-check, /intelligence-writing, /writing-assessments and /threat-actor-profiling.

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Use when assigning a confidence level to an analytical judgment, the user asks "how confident are we?" / "what is the confidence on X?", or the orchestrator's tradecraft pipeline calls for a confidence level before publishing. Provides three named levels (High, Moderate, Low) with 0-100 score ranges aligned to STIX, and the rule that confidence cannot exceed what the weakest load-bearing claim supports.

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Use when phrasing a forward-looking statement, the user asks "how likely is X?" / "what's the likelihood?", or the tradecraft pipeline applies a probability yardstick to a finished product. Standardised likelihood language across all products.

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Detect and remove the tells of AI-generated writing in BOTH English and Spanish, and read back the evidence honestly. Use when the user asks to "de-AI" / "humanize" / "un-slop" a draft, to examine whether text carries the tells (delve, tapestry, "it's not just X, it's Y", "here's the thing", em-dash overuse, an assistant's own closing line left in the document), to compare documents for overlap, or mentions signs-of-ai / SignsOfAI. Backed by the SignsOfAI engine — for a measured 0–100 score, sentence-rhythm burstiness, originality, citations, a writer baseline or perplexity, hand off to that engine (web app, CLI or MCP server) as described below. It cannot determine who wrote a text and must never imply that it can.

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Iterative literature-review workflow for a research topic. Use this skill to draft up to 10 search keywords, build a seed set from OpenAlex title-and-abstract matches, expand by backward and forward citations, screen candidates by title and abstract, repeat until no new relevant papers remain, rank the final set, inspect up to 30 full texts, build a concept-reference knowledge graph, and write a literature review grounded only in the final included references.

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Generates Claude Code plugin agent .md files: writes YAML frontmatter (name, model, color, tools, hooks, disallowedTools), crafts system prompts, and creates triggering example blocks with context and commentary. Validates agent structure against naming, length, and format constraints. Use when the user asks to create an agent, add an agent, write a subagent, configure agent frontmatter, design agent system prompts, set agent tools or colors, build an autonomous agent, or add agent hooks.

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Create/update .agent/constitution.md. Use when commands/boundaries/constraints must be confirmed before baseline or code changes. Draft v0 from repo evidence, then interview user.

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Agent-native design engine that makes AI do more useful work: route the prompt, fork a template, weave IFQ ambient craft, verify the artifact, and only install export tooling when requested. One prompt -> shippable HTML, with optional MP4 / GIF / PPTX / PDF / SVG. Triggers include prototype, hi-fi mockup, slide deck, motion demo, infographic, dashboard, whitepaper, changelog, business card, social cover, brand from scratch, design critique, mp4/gif export, 60fps, keynote, PPTX, A-vs-B benchmark. Do not use for production web apps, SEO-critical sites, backend systems, or pure copy edits.

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Draft privacy policies, terms of service, disclaimers, and legal notices. Creates GDPR-compliant texts, cookie policies, and data processing agreements.

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Open Source License guidance, selection, compliance review, and drafting. Use this skill when users ask about choosing open source licenses, checking license compatibility, reviewing projects for OSS compliance, generating LICENSE/NOTICE files, or understanding specific license terms. Triggers include questions about MIT, Apache, GPL, BSD, LGPL, AGPL, copyleft, permissive licenses, license compatibility, SPDX identifiers, or any OSS licensing topic.

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Investor And Board Communication Specialist. Use to draft monthly investor updates, quarterly board decks, and high-signal stakeholder communications that surface wins, misses, risks, and asks clearly.

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Generate production-ready business documents including freelance contracts, project proposals, SOWs, NDAs, and MSAs with jurisdiction-aware clauses. Covers US (Delaware), EU (GDPR), UK, and DACH (German law) legal frameworks. Includes contract templates, clause libraries, and DOCX conversion. Use when starting client engagements, writing proposals, drafting partnership agreements, or needing GDPR-compliant data processing addenda.

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Accelerator Application Specialist. Use to shortlist startup programs, draft applications, prepare founder videos, and rehearse accelerator interviews with a disciplined founder narrative.

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Prose quality checker for Quarto (.qmd) files, grounded in William Zinsser's *On Writing Well* (30th Anniversary Edition). Checks for clutter, weak verbs, hollow qualifiers, clichés, inflated academic voice, poor leads and endings, pronoun and tense inconsistency, and unclear explanation. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to improve prose quality, tighten writing, reduce clutter, or apply Zinsser's writing principles to a draft. For grammar and punctuation, use the proofread skill. For APSA style rules, use the apsa-style skill. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.

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"Apply the Elaboration Likelihood Model to design persuasion strategies by matching message type to audience elaboration level. Use this skill when the user needs to craft persuasive communications, choose between argument-based and cue-based messaging, predict attitude durability after a campaign, or when they ask 'why did the message fail to persuade', 'how to change resistant attitudes', or 'should we use data or endorsements'.".

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Design and draft multi-email sequences with full copy, timing, branching logic, exit conditions, and performance benchmarks. Use when building onboarding, lead nurture, re-engagement, win-back, or product launch flows, when you need a complete drip campaign with A/B test suggestions, or when mapping a sequence end-to-end with a flow diagram.

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Draft marketing content across channels — blog posts, social media, email newsletters, landing pages, press releases, and case studies. Use when writing any marketing content, when you need channel-specific formatting, SEO-optimized copy, headline options, or calls to action.

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Review content against your brand voice, style guide, and messaging pillars, flagging deviations by severity with specific before/after fixes. Use when checking a draft before it ships, when auditing copy for voice consistency and terminology, or when screening for unsubstantiated claims, missing disclaimers, and other legal flags.

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Multi-source research on a customer question or topic with source attribution. Use when a customer asks something you need to look up, investigating whether a bug has been reported before, checking what was previously told to a specific account, or gathering background before drafting a response.

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Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.

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"Enterprise risk management (ERM) framework layer — integrates COSO ERM 2017 (five components, 20 principles), ISO 31000, three-lines model, risk appetite, risk heatmap, and key risk indicators (KRI) into a complete governance playbook covering structure through culture. Use for ERM implementation, risk-system build, risk mapping, risk-appetite statement drafting, three-lines setup, CRO role design, or Taiwan FSC corporate-governance evaluation response. Triggers: 『ERM 導入』『風險管理框架』『COSO』『風險地圖』『風險胃納』『KRI』『CRO 職責』『三道防線』『風險委員會』『ISO 31000』『風險熱圖』『風險治理』. For 師大／政大／陽交 EMBA risk-management/governance/audit cases. Complements Asgard `algo-risk-*` (Altman Z, Benford, credit, VaR) with the framework/governance layer. 獨董挑選/董事會組成/IPO 治理: use `biz-corporate-governance`.".

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