「decide」の検索結果

Ask Daniel a blocking decision as options with a recommendation and honest pros/cons, rather than prose. Use whenever work is blocked on a judgment call, a product decision, an approval, or a choice between approaches — instead of writing "let me know which you prefer" at the end of a message.

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N-round adversarial review pipeline for empirical research output — the chain from data to LaTeX tables to a manuscript that cites them. A Claude drafter proposes minimal diffs, a deterministic mechanical battery gates every diff from a clean state with a regression gate, a Codex reviewer files check-backed critiques, and a blind judge panel decides residual disputes. Manual-invoke ONLY: trigger when the user explicitly runs /adversarial-empirical-review or names 'adversarial-empirical-review' / 'adversarial empirical review'. Do NOT auto-trigger on generic 'review my results', 'check my tables', or manuscript-editing requests. For prose-style refinement use style-emulation instead; this skill AUDITS WHETHER THE TABLES ARE CORRECT — that each number in the tables is what the analysis code computes, reproduces from the data, and is internally consistent. It is an empirical + code review: the manuscript is read only to resolve table numbering, and prose is not examined.

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Use when a task needs the judgment of a dermatologist — triaging a pigmented lesion for melanoma risk, choosing a biopsy technique and reading the pathology in clinical context, staging a skin cancer to decide margins or Mohs referral, escalating psoriasis/eczema treatment by severity score, or managing isotretinoin risk under REMS/iPLEDGE rules.

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Audit an existing mathematical, logical, algorithmic, or technical proof from its stated conclusion backward as a bounded AND/OR graph of exact obligations. Use to reconstruct conclusion dependencies, determine whether a proof-supplied route establishes the conclusion, or expose hidden assumptions, unmet side conditions, cycles, overly strong steps, or silent route switches. For a source-mapped Lamport rendering use convert-lamport, and for forward hierarchy, construct, and scope conformance use forward-lamport before this skill. This does not decide full theorem-level entailment by searching for a different proof; do not turn the audit into a linear reversed proof, exhaustive proof search, or replacement proof.

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Three-agent adversarial debate protocol for strategic decisions. Two advocates steelman opposing positions while a moderator identifies risks and synthesizes a binding consensus. Use when choosing between alternatives, evaluating tradeoffs, or making high-stakes decisions.

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Build Opportunity Solution Trees using Teresa Torres' framework for structured product discovery. Use this skill when: - You need to map a desired outcome to opportunities, solutions, and experiments - You want to decide WHAT to build next based on user research and discovery data - You have workshop findings, pilot feedback, or user research to structure into actionable options - You need a visual tree diagram showing the path from outcome to testable experiments

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Prioritize a feature backlog or list of ideas. Use when the user says "help me prioritize", "prioritize this backlog", "RICE score these", "MoSCoW", "opportunity solution tree", "what should we build first", "rank these features", or has a list of items and needs to decide order - even if they don't explicitly say "prioritization".

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Allocate testing effort based on risk and failure likelihood using Google's SET/SWE/TE model. Use when user says "risk-based testing", "where should I focus testing", "test coverage strategy", "prioritize what to test", "high risk areas", or needs to decide how to distribute QA effort across a codebase - even if they don't explicitly say "risk-based".

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Structure and run a post-interview candidate debrief. Use when the user says "run the debrief", "how do we decide on this candidate", "let's calibrate", "we need to make a hire/no-hire call", "prep the debrief meeting", or wants to structure the decision-making process after interviews are complete - even if they don't explicitly say "debrief". Also use when a recruiter wants to prevent groupthink or HiPPO effect (highest paid person's opinion) from dominating the decision.

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Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when interacting with gcsfuse: decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and config files, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or fully POSIX-compliant shared file systems (Filestore, Managed Lustre).

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Use this skill when creating or managing queues, configuring queue membership, setting up case or lead queues, creating public groups, or using groups in sharing rules and manual sharing. Trigger keywords: queue, public group, queue membership, queue email, group sharing, case queue, lead queue. NOT for the rule that decides which queue a record lands in — use admin/assignment-rules. NOT for Omni-Channel routing configuration — use admin/omni-channel-routing-setup.

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Run work as an explicit event-driven state machine executed by subagents. The orchestrator is the runtime from the canonical loop — `state, effects = init(machine); execute(effects); while state is active: event = nextEvent(); state, effects = transition(machine, state, event); execute(effects); return state.output`. All routing judgment is authored ONCE, at plan time, into a machine file (states, event alphabet, transition table, budgets, final states); at runtime the orchestrator does pure table lookups and dispatches effects — it never decides, never authors, never ingests artifacts. Subagent/sync protocol is the timeboxed-iterating one: role prompts scaffolded once to disk and dispatched BY PATH, an initialiser preamble every subagent reads first, a self-populating cheatsheet, per-unit files, tiny structured returns, independent measurement gate. Use when the user says "workmachine", "run this as a state machine", "state-machine this", or when a goal has a small number of clearly named phases with explicit outcomes (built / passed / failed / blocked) and you want the routing to be auditable rather than judged on the fly. For clock-driven loops use timeboxed-iterating; for wide graphs with judged edge criteria use workgraph.

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Catalog-then-fix slop removal on an existing prose draft. Parallel catalog subagents inventory four slop categories (theatrics, overwrought register, corrective antithesis, dramatic short sentences), fix subagents repair only what a catalog names, mechanical lint + frequency analysis bracket the run, and a regression gate (lint delta, word count, cold meaning check) decides whether the result ships. Use when the user says "deslop this draft", "catalog deslop", "strip the AI patterns from this file", or as the final stage of the article-factory and mosaic-writing skills. For writing or redrafting prose from scratch, use the prose skill instead - this skill only repairs an existing draft in place.

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Structured Zettelkasten workflow for AMD — observe, draft, enrich, retrieve, decide, preview, write, verify. Produces high-quality atomic knowledge cards with deliberate linking.

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Search Taobao/Tmall, inspect products, select SKUs, add to cart. Persistent browser session with stdin/stdout JSON protocol. AI decides, script executes.

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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

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Audit and curate the `learnings` memory namespace — the one namespace nothing re-derives, so the only one that rots. Runs moflo's mechanical audit to nominate stale, unused, and near-duplicate entries, then decides entry by entry whether to keep, retire, compress, or merge, and propagates the result to the shared artifact. Use when memory search returns stale or duplicated hits, after retiring a big chunk of work whose supporting entries went stale with it, or as a periodic pass once the namespace passes a few hundred entries.

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Research and ideation partner for GAME DESIGN — think through design ideas before writing them into the GDD; produces a brief, never edits the GDD itself. Use to assess a genre or market for viability, dissect a reference game (mechanics → dynamics → aesthetics), explore how to improve or extend an existing system, flow, or content type, research new mechanics the design lacks, investigate a part of the GDD in code, or develop the research bucket of a /unikit-gd-review report into decided edits. Trigger on "explore how to improve the flow", "ways to improve the combat system", "is this genre saturated", "break down the combat of Hades", "work out the review's open questions". GAME-DESIGN research only — for CODE or technical research use /unikit-explore; to reconstruct a design from code use /unikit-gd-recon; to write a change into the GDD use /unikit-gd-system or /unikit-gd-spec; to apply edits you know use /unikit-gd-apply; to invent a new game use /unikit-gd-brainstorm.

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First-pass strategic-orientation review of a repository. Produces an evidence-cited map (not a grade) calibrated to a reference class, helping the user decide where to engage, where to tread carefully, and where to leave alone. Advisory only — no changes made.

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Router for the frontend design stack. Use at the start of any frontend UI task (build a page or component, redesign, pick a style or palette, polish, audit, animate, review UI) to decide which installed skill leads, which ones support, and which rule wins when the packs disagree. Also use when two design skills give contradicting advice.

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One page, hands-on manual tier — drive a live page through the web accessibility (a11y) checks a rule engine can't decide: keyboard operation and focus order, screen-reader names, roles and states from the accessibility tree, reflow and zoom, reduced motion, form errors, and target size. Grades each finding by evidence basis (verified / confirm-with-a-human / human-required) and severity, and closes every criterion in a ledger: verified, flagged, not exercised, or N/A. Locates and assesses; does not fix (use `accessibility-fix`). Use it for keyboard testing, focus-order checks, screen-reader or a11y-tree review, reflow and zoom at 200%, or 'is this operable, not just lint-clean'. The automated tier is `accessibility-scan`; `accessibility-audit` runs both across a sampled site.

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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

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Diagnose GitHub bug reports in wordbricks/onequery. Use when given a GitHub issue URL from wordbricks/onequery and asked to decide next steps such as verifying against the repo, requesting more info, or explaining why it is not a bug; follow any additional user-provided instructions.

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Check a change for performance regression against this machine's recorded baseline - decide whether the diff needs checking, run the deck benchmark under the hygiene wrapper, and attribute any regression to an element. Use before opening a PR that touches the simulation hot path.

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