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概要と使いどころ
Use when adding, adopting, debugging or updating Morphir CLI examples and morphir itest scenarios, including scenarios.md, .feature.md and .feature files, scenario metadata, Rego assertions and integration coverage.
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。
Secular technology trends, technology adoption cycle, disruption risk, AI impact analysis, digital transformation, industry 4.0 trends, technology moat, innovation trajectory, R&D effectiveness, tech competitive positioning
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。
Think and work like an expert Geomagnetist. Use when a task calls for Geomagnetist judgment. Reasons from spherical-harmonic main-field theory and remanence physics through IGRF-14/WMM2025 vs CHAOS-8 SV, INTERMAGNET baseline adoption (IBFV2.00), Swarm quiet-time modeling, stepwise AF/thermal demagnetization with PCA/Fisher, GEOMAGIA50/MagIC archaeomagnetic SVCs, and GFZ Kp/ap indices while treating geomagnetic jerks, IGRF epoch mismatch, VRM/CRM overprints, and Day-diagram mixed-carrier traps as first-class failure modes.
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。
Think and work like an expert Agroecologist. Use when a task calls for Agroecologist judgment. Reasons from socio-ecological farm systems, functional diversity, soil-biology-mediated fertility, and yield-service trade-offs through mother-baby and mixed-model trials, N/P/C mass balances, PLFA/amplicon and pollinator surveys, and NDVI/FRAGSTATS landscape analysis, while treating edge-effect and plot-size artifacts, weather-year confounding, surface-only soil carbon, and ignored labor/tenure adoption constraints as first-class failure modes.
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。
Research npm packages — download stats, dependencies, maintainers, version history, and security advisories. Useful for technology due diligence, dependency auditing, and evaluating package reliability before adoption.
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。
Guided setup and upgrade-check experience for Lattice projects -- scans the repository, detects existing configuration and outdated conventions, suggests refiners and available upgrades in priority order, and creates or reconciles the .lattice/ config. Bridges the gap between installing skills and getting first value, and between upgrading Lattice and adopting its newest conventions. Use when the user says 'lattice init', 'set up lattice', 'initialize lattice', 'get started with lattice', 'configure lattice for this project', 'check for lattice upgrades', or 'upgrade lattice conventions'.
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。
Use after receiving WebGPT or another LLM review on a Formax todo and before sending the todo back for another pass. Produce a concise handoff response that says what we adopted, what we reject or question, and what the reviewer should specifically re-evaluate in `docs/todolist.md`.
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。
Build customer case studies as marketing and chasm-crossing reference assets during PRD v1.0 Market Adoption. Triggers on requests to build case studies, produce customer stories, create reference content, or when user asks "build a case study", "customer story", "reference account", "case study interview", "before/after story", "social proof page", "logo wall". Outputs CFD-CASE-* evidence entries, GTM-CASE-* marketing assets, and updates ADO-REF-* with story status.
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。
Install the PRD-Driven Context Engineering methodology into a fresh OR existing repository — the subscription-native alternative to forking the whole repo. Runs an interactive wizard that seeds the framework (.claude/ hooks, skills, agents, rules, scripts) without clobbering product content. Triggers on "install the methodology", "adopt this into my repo", "self-install", "set up PRD lifecycle here", "onboard existing project". Outputs an installed framework + a verification report.
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。
Apply Rob Fitzpatrick's Mom Test discipline to customer interviews during PRD v1.0 Market Adoption. Triggers on requests to interview customers, run discovery calls, validate ideas with users, or when user asks "how do I interview customers?", "Mom Test", "Rob Fitzpatrick", "customer interview", "user research without lies", "talking to humans", "discovery conversation". Outputs CFD-* discovery entries with Mom Test-calibrated confidence.
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。
Establish weekly customer-discovery cadence and Opportunity Solution Tree practice using Teresa Torres's Continuous Discovery Habits framework during PRD v1.0 Market Adoption. Triggers on requests to set up discovery cadence, build opportunity solution tree, run weekly customer interviews, or when user asks "Torres", "continuous discovery", "opportunity solution tree", "outcomes vs outputs", "weekly interviews", "assumption mapping". Outputs CFD-* discovery entries and updates to ADO-STAGE-* and PER-* with new evidence.
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。
Systematically harvest short testimonials from customers via NPS, milestones, post-purchase, and email during PRD v1.0 Market Adoption. Triggers on requests to collect testimonials, set up social proof harvest, gather customer quotes, or when user asks "how do we get testimonials?", "social proof harvest", "NPS responses", "testimonial wall", "customer quotes", "post-purchase survey", "milestone follow-up". Outputs CFD-TST-* testimonial entries and GTM-TST-* placement assets.
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。
Validate system resilience through controlled fault injection. Covers hypothesis-driven chaos experiments, failure injection types (network, service, infrastructure, dependency), LitmusChaos/Chaos Mesh/AWS FIS/Gremlin/toxiproxy tooling, automated abort gating, game day planning, and progressive chaos adoption. Use when: "chaos engineering," "fault injection," "resilience test," "game day," "failure recovery," "system reliability," "blast radius." Not for: safe rollout flags/canary/dark launch during a release — use testing-in-production; designing new tests from production telemetry — use observability-driven-testing. Related: testing-in-production, observability-driven-testing, performance-testing, release-readiness, test-environments.
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。
Audit whether a paper's EVALUATION DESIGN actually measures what it claims and whether its reporting is complete — the validity layer family D (experiment-forensics) cannot reach. Three patterns: train/test leakage means the reported score may not measure generalization (HP-EVAL-LEAKAGE — adopts the Kapoor & Narayanan 8-type / 3-category leakage taxonomy; the illegitimate-proxy / sampling-bias / pretraining-contamination subtypes hand off as needs_external_check, naming but NEVER running Oren-2023 exchangeability / Shi-2023 Min-K% / Golchin-2023 Time-Travel / BIG-bench canary); a load-bearing LLM judge is conflicted (same model/family as a compared system) or unvalidated (no human-agreement, no bias control) (HP-JUDGE-VALIDITY); a declared condition/metric is dropped or switched to favor the method, or 'best' is chosen with no held-out set (HP-SELECTIVE-REPORTING). Verdict-bearing at L0/L1 from the DESCRIBED protocol — NOT repo-gated like experiment-forensics; L2 only CONFIRMS against split/preprocessing/result files. A fresh cross-model reviewer (gpt-5.6-sol xhigh, read-only, fresh thread per pass) PROPOSES findings, each span-anchored to a ledger claim_id; tools/adjudicate_findings.py DECIDES the verdict. Leakage and under-reporting are usually HONEST methodological errors — every finding describes a discrepancy to CHECK, never an accusation. An LLM generating GROUND-TRUTH labels is HP-FAKE-GT (experiment-forensics) — routed there, not here. Emits eval-design-forensics.findings.json; computes NO verdict. Detect-only. Triggers: "eval design audit", "evaluation validity", "train/test leakage", "data leakage", "is the score measuring generalization", "LLM judge bias", "is the judge validated", "selective reporting", "cherry-picked results", "评估设计审计", "评测有效性", "数据泄漏", "训练测试集泄漏", "裁判模型有没有验证", "选择性报告".
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。
Analyzes an AI/ML publication — paper, preprint, article, technical blog post — and extracts what an enterprise AI engineer should do about it. Use when someone supplies a URL or document on RAG, embeddings, fine-tuning, prompt engineering, agents, or LLM deployment and asks "review this paper", "what do you make of this", "is this worth adopting", or "summarise the method and its limits". The subject matter must itself be machine learning.
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。
Use when asked to take over, adopt, or babysit a GitHub pull request until it merges — read review feedback, fix it, resolve threads, dismiss unreasonable change requests, and merge once approved and green. Picks between driving the PR live in this session or handing it to the Looper daemon for unattended background runs, confirming with the user when unclear. Triggers on "take over this PR", "接管这个 PR", "持续修复 review 直到合并", or a Looper takeover bot comment. Works in any coding agent (Claude Code, Codex, opencode, Gemini, …) using gh + git.
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。
Review trust before frontend tooling adoption.
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。
Suede-owned prospecting and qualification discipline. Use when defining an ICP, sourcing and enriching a bounded lead list, finding early adopters or design partners, scoring account fit, or documenting disqualification evidence. NOT FOR: sending outreach (use suede-cold-email), changing CRM routing (use suede-revops), or profiling competitors instead of prospects (use suede-competitor-profiling).
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。
Suede-owned operations-assessment discipline that maps how work actually happens before anyone designs a system: floor-level interviews with the people who do the work, an inventory of every silo including spreadsheets and inboxes used as databases, friction quantified in the requester's own numbers, opportunities ranked by annual value against build complexity, and adoption watched for the thirty days after launch. Use when nobody can answer what to automate, when an operation needs auditing before a build, when tribal-knowledge and key-person risk has to surface, or when a shipped system is quietly being routed around. NOT FOR: deciding what to build and in what order once the map exists (use suede-ops-architecture); researching external customers rather than internal operators (use suede-customer-research); lead lifecycle, scoring, and CRM routing rules (use suede-revops); product instrumentation and dashboards (use suede-analytics); getting a new user to first value (use suede-onboarding).
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。
Suede-affiliated engineering-as-marketing strategy for selecting, scoring, and scoping calculators, graders, generators, and other free interactive tools. Use when the user wants a lead, link, education, or product-adoption asset with a measurable path to the paid product. NOT FOR: downloadable lead assets (use suede-lead-magnets), implementation of a full website (use suede-site-alchemy), or search diagnostics (use suede-seo-audit).
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。
Evidence-driven web and open-source research for questions that require multiple sources, factual verification, comparisons, or an adopt/adapt/build decision. Use for substantial research in foreground sessions, the genesis-researcher subagent, and research-profile background sessions. Skip for a single stable fact or a known URL that only needs fetching.
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。
Context-driven AI development with AGENTS.md, repo knowledge bases, Claude Code, Codex, and Copilot. Use when adopting repo-native AI workflows or multi-repo setups.
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。
Brownfield onboarding — audits existing project artifacts for template format compliance (not just existence), classifies gaps by impact, and produces a numbered migration plan. Run this when joining an in-progress project or upgrading from an older template version. Distinct from /project-stage-detect (which checks what exists) — this checks whether what exists will actually work with the template's skills.
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。
Set up, adopt, refresh, or audit a repository's agent instructions (the AGENTS.md block) so AI agents work well in that repo. Also records observed agent mistakes as pitfalls. Use when invoked by name
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。