「proven」の検索結果

Vet a new or changed third-party dependency for license, provenance, and supply-chain risk before any install runs.

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Analyze liquid markets with a strict ICT/SMC framework that combines multi-timeframe bias, liquidity sweeps, displacement, close-confirmed MSS/BOS, FVG/OB/Breaker/OTE retracements, premium-discount location, session timing, invalidation, targets, and risk-to-reward. Use for ICT chart reviews, live-market analysis, OHLCV scans, or validating a user's trade thesis. Return an auditable setup status and conditional plan; do not use for generic indicator analysis, order execution, or claims of proven institutional intent.

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Suede Labs skill that finds and organizes the rights gaps in a creator project before packaging: ownership, contributors, splits, samples, licenses, provenance, metadata, licensing readiness, and royalty-routing readiness, each marked confirmed or unknown against an evidence trail. Use when a song, release, or creative project needs a rights check before registry, licensing, sync, or payout discussion; when splits, sample clearance, or chain of title are unclear; or when someone asks whether they have the rights to release, license, or get paid for a work. Organizes evidence only: clears no rights, confirms no ownership, moves no money, writes to no registry. NOT FOR: building the transfer package itself (use suede-rights-passport); linting a release folder's files and metadata (use suede-release-linter); a sync one-sheet or pitch (use suede-sync-packaging).

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Plan, write, art-direct, generate, and package a coherent 2-10 image minimal-zine social series from notes, articles, photographs, travel stories, products, reviews, cultural topics, data, PDFs, or mixed subjects. Use for Xiaohongshu/小红书图片, Instagram carousels, social visual essays, recommendation posts, photo diaries, evidence-backed explainers, or any multi-image editorial sequence. Produces analysis, card roles, subject-aware composition, saved prompts, real raster images, natural caption copy, evidence provenance when needed, and series-level QA.

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Comprehensive brand messaging, positioning, and value proposition development using proven frameworks including Peep Laja Message Layers, Osterwalder Value Proposition Canvas, Geoffrey Moore positioning, April Dunford's Five Components, StoryBrand SB7, Andy Raskin Strategic Narrative, and Messaging House. Use when developing brand identity, brand messaging architecture, positioning statements, value propositions, messaging hierarchies, brand pillars, taglines, one-liners, elevator pitches, brand guidelines, visual identity systems, or creating Positioning & Messaging Packs. Triggers include: messaging framework, brand positioning, value prop, messaging architecture, brand pillars, brand identity, StoryBrand, positioning statement, brand guidelines, design system, messaging house, corporate identity, brand voice, visual standards.

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Data-model rules that make a schema importable from day one, so the migration-import-engineer is never blocked on missing columns. Every SMB Product-Builder product must let a customer bring their data from an incumbent (ServiceTitan/Toast/Mindbody/Shopify) — that requires provenance (source_ref) and rollback (import_batch_id) on importable entities, and modelling real-world actors as entities rather than inline fields. Applied by architect when writing the data model in ARCH-{slug}.md, and checked by migration-import-engineer. One cheap rule set prevents the migration↔architecture seam gap from recurring across all 40 products.

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Reviews a change before it is merged, from little or no input. With nothing typed it reviews the branch you are on, uncommitted work included, against its base, its PR and its ticket, so a developer can check their own work before asking for review. With PR links, repo#N or a branch it reviews someone else's change the same way, several repos at once. It judges the failed CI checks and every Bugbot and reviewer comment, gets a fresh breaker review, traces every other piece of code that uses what changed, proves each finding or marks it unproven, says what the merge needs (a build, env vars, migrations, deploy order) and how to check the deploy, never posts to GitHub, and offers fixes only after the report. Runs only when the user types it.

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Writes or updates engineering documentation and architecture decision records from repository facts, explicit assumptions, trade-offs, and verification links. Use for README changes, design docs, runbooks, ADRs, migration notes, and contributor documentation. Not for implementation planning alone or for copying external documentation without provenance.

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Prepares and controls software releases with risk classification, CI quality gates, artifact provenance, feature flags, staged rollout, measurable promotion and rollback thresholds, post-deploy verification, and cleanup. Use for deployment pipelines, launch readiness, canaries, production rollout, release automation, or rollback planning. Not for merely merging a completed development branch or proving one local change.

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Verifying spec compliance: extracts ACs from specs, adversarially checks conformance, generates BDD scenarios and traceability matrices. Use when impl must be proven to match a PRD/SRS/AC.

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Apply evidence-first engineering discipline to any agent-built software project: fact discovery before action, evidence-calibrated status reporting, explicit change boundaries and stage gates, controlled confirmation for risky or external actions, sensitive-information redaction for anything shared publicly, and resumable continuity after interruptions. Use when users ask an agent to take over an existing codebase, deliver a feature across stages, verify whether work is actually complete, judge release readiness, or keep conclusions honest about what is proven versus assumed. This foundation skill is domain-neutral; vertical suites (for example mini-program engineering) build on it by adding domain facts and platform rules.

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Dispute resolution, forensic investigation, and risk assessment for autonomous AI agent transactions. Reconstruct provenance chains, adjudicate fault, generate actuarial risk profiles for agent insurance. The accountability layer of the Agent Trust Stack.

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Expert guide for AI Safety, Governance, and Responsible AI in production — Constitutional AI enforcement, runtime guardrails (NeMo Guardrails 2.0, Llama Guard 3), bias auditing, hallucination detection, EU AI Act compliance, model cards, and content provenance / Panduan ahli untuk Keamanan AI, Tata Kelola, dan AI Bertanggung Jawab di produksi.

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Manages a Zotero academic reference library through both the local API (localhost:23119, read-only) and the Web API (api.zotero.org, read-write), using a structured collection hierarchy (Inbox / Active Projects / Background / Reading Queue / Archive / Meta) plus project, status, priority, and type tags. Handles adding papers with full metadata, deduplication, attaching provenance notes, moving items between collections, updating tags after reading, listing the prioritized reading queue, and setting up the literature scaffold for a new project. Use when the user asks to add / save / file / organize a paper in Zotero, check / list / clean up the reading queue, move papers between collections, tag papers for a project, query their library ("what do I have on X?"), or set up Zotero for a new research project.

日本語の概要は準備中です。原文の説明を表示しています。

Provides compliance, governance, and supply chain security guidance for cloud-native systems. Covers OPA Rego policies, Kyverno cluster policies, SBOM generation, SLSA provenance, audit trail design, and regulatory framework mapping. Use when user mentions 'compliance', 'governance', 'OPA', 'kyverno', 'SBOM', 'SLSA', 'audit', 'policy-as-code', 'SOC2', 'HIPAA', 'PCI-DSS', 'artifact signing'.

日本語の概要は準備中です。原文の説明を表示しています。

Parallel agent fleet dispatch with progress tracking and result aggregation. Launch N agents, monitor completion, merge results. Proven at 7-agent scale.

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A survey of the best-known active scientific controversies in nutrition — saturated fat and cardiovascular disease, dietary cholesterol, low-carb vs low-fat, ultra-processed foods, red meat and cancer, salt and blood pressure, and the replication status of popular single-nutrient claims. Use when a question asks whether a widely reported nutritional claim is settled, or when the department needs to distinguish "contested but plausible" from "settled" from "disproven."

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Markdown to HTML/PDF build + FTP sync to configured remote host. Pandoc + xelatex templates, branded output, automated deployment. Proven on 29-document HEL series.

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Evaluating the quality, provenance, and relevance of evidence that supports or undermines a claim. Covers source credibility, sampling quality, study design, levels of evidence (anecdote to meta-analysis), base rate integration, distinguishing primary from secondary sources, and calibrating belief to evidence strength. Use when the question is not whether an argument is valid but whether its premises are actually supported by the available data.

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Load, validate, and use DACP bundles as structured execution context. Detects .bundle/ companion directories, validates integrity (manifest schema, fidelity, provenance), loads typed data, and builds ExecutionContext for receiving agents. Scripts are NEVER auto-executed. Use when processing incoming DACP bundles, interpreting .bundle/ directories alongside .msg files, validating bundle integrity, or building execution context from bundle payloads.

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Integrate multiple source findings into an attributed synthesis or comparison. Use for combine these summaries, synthesize results, merge findings or multi-source analysis. Preserve claim-level provenance, coverage, qualifiers, conflicts and uncertainty rather than repeatedly compressing narrative summaries.

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When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' or 'ideas to grow.' This skill provides 140 proven marketing approaches organized by category.

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Apply systematic problem-solving techniques for marketing challenges including campaign complexity (simplification cascades), creative blocks (collision-zone thinking), recurring campaign patterns (meta-pattern recognition), assumption constraints (inversion exercise), audience scale uncertainty (scale game), and dispatch when stuck. Techniques derived from proven problem-solving frameworks adapted for marketing execution.

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OCRs scanned or image-only corpora with vision-language models in three phases. Evaluate selects a system by measured CER or WER against stratified human ground truth. Run builds the production pipeline. Clean corrects raw OCR with LLM and rule-based passes, quality diagnostics, and span-level provenance. Use when choosing an OCR model for a corpus, measuring OCR accuracy, transcribing scans at scale, or correcting raw OCR. Born-digital documents with text layers go to doc-to-markdown.

日本語の概要は準備中です。原文の説明を表示しています。