「bounded」の検索結果

Build a bounded CI contract gate for an Attio integration using fixtures, schema checks, and an optional read-only smoke request. Use when Attio changes need pull-request evidence without mutating CRM data. Trigger with "Attio CI", "test Attio integration", or "Attio pull request gate".

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 and review a bounded CI gate for Algolia index configuration and disposable-index smoke tests. Use when search changes need pull-request evidence without mutating production. Trigger with "Algolia CI", "test Algolia in GitHub Actions", or "search deployment gate".

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。

Collect a bounded, secret-safe Algolia diagnostic bundle for an incident or support escalation. Use when a reproducible search or indexing failure needs portable evidence. Trigger with "Algolia debug bundle", "collect Algolia diagnostics", or "Algolia support 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。

Monitor and optimize Algolia request pressure using observed responses and bounded client behavior. Use when requests return 429, queues grow, or search and indexing compete for capacity. Trigger with "Algolia rate limit", "Algolia 429", or "throttle indexing".

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。

Design account-aware Alchemy throttling, bounded retries, and admission control from observed throughput rather than stale plan constants. Use when preventing or handling rate limits. Trigger with "Alchemy rate limit", "Alchemy throughput", or "fix Alchemy 429s".

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Establish a deterministic local EVM development loop with pinned forks, synthetic fixtures, and bounded Alchemy usage. Use when adding local chain tests or repairing flaky fork-based development. Trigger with "Alchemy local dev", "Hardhat fork with Alchemy", or "pin a mainnet fork".

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。

Design isolated Algolia development, staging, preview, and production targets with explicit promotion rules. Use when environments share credentials or index names, or previews need bounded search data. Trigger with "Algolia environments", "Algolia staging setup", or "preview index".

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Classify Alchemy authentication, JSON-RPC, Data API, throughput, and partial-response failures before applying bounded recovery. Use when an Alchemy integration fails or degrades. Trigger with "Alchemy error", "Alchemy 429", or "debug an Alchemy request".

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。

Classify Adobe failures from redacted response evidence and select the smallest bounded recovery. Use across auth, Firefly, Photoshop, PDF Services, Events, and App Builder. Use when the task requires adobe response-led error triage. Trigger with "fix Adobe error", "Adobe 403", or "Adobe API failed".

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Run a bounded Abridge smoke test through the documented user workflow using an approved test encounter and no invented API. Use when validating a new tenant or pilot cohort. Trigger with "smoke test Abridge".

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Implement service-specific Adobe admission control, Retry-After handling, bounded retries, and spend-aware queues. Use when scaling workloads or handling 429 responses. Trigger with "Adobe rate limit", "Adobe 429", or "Adobe backoff".

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Analyze and design idempotency, bounded polling, per-service circuits, durable queues, DLQ/replay, degradation, and reconciliation for Adobe workloads. Use when the task requires adobe async reliability controls. Trigger with "Adobe reliability", "Firefly retry design", or "PDF job recovery".

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。

Create narrow, version-pinned Adobe SDK and REST adapters with typed contracts, redaction, bounded polling, and compatibility evidence. Use when writing or upgrading integration code. Trigger with "Adobe SDK patterns", "wrap Adobe API", or "review Adobe client".

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。

Analyze an input repeatedly without a termination condition

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Create safety-bounded draft structures and run local deterministic checks for clinical case, diagnostic, trial, safety, and aggregate research reports. Use only with synthetic, de-identified, or aggregate inputs and verified source-fact manifests; every output requires qualified review.

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Formulate evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Use when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.

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Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments. Use for authorized review of scientific manuscripts, protocols, preprints, or research proposals; reporting-guideline selection; claim–evidence checks; methods, statistics, reproducibility, ethics, figure/table, and citation critique; or revision-response planning.

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Organize business and technology teams for fast flow using Skelton & Pais's "Team Topologies". Use when the user mentions "team topologies", "Conway's law", "platform team", "stream-aligned team", "team boundaries", "cognitive load", "how should we split teams", "who owns this service", "team dependencies", or "reorg". Also trigger when reorganizing engineering teams, aligning team and service boundaries, splitting a monolith and deciding ownership, reducing cross-team handoffs, or designing an internal platform. Covers the four team types, three interaction modes, the inverse Conway maneuver, and fracture planes. For bounded contexts, see domain-driven-design. For dependency direction in code, see clean-architecture.

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Guided journey from a large aged codebase everyone fears to touch to one that is safe to change, legible, bounded, and resilient - paid down in place without a rewrite. Orchestrates eight skills phase by phase - working-with-legacy-code, refactoring-patterns, clean-code, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, domain-driven-design - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, REMOVE-TECHNICAL-DEBT-PLAN.md) so the journey resumes across sessions. Use when the user wants to tame a legacy codebase, pay down technical debt safely, avoid a big-bang rewrite, or says 'we are afraid to touch this code'. For a fresh vibe-coded prototype, improve-code-quality; for greenfield structure, design-code-architecture; for a product-and-UX pass, improve-app; to optimize a working codebase for speed, architecture-optimization. For one framework in isolation, invoke that skill directly.

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 journey from a working codebase grown slow and tangled to one measurably fast, cleanly bounded, and readable. Orchestrates eight skills phase by phase - working-with-legacy-code, clean-architecture, software-design-philosophy, refactoring-patterns, system-design, ddia-systems, release-it, pragmatic-programmer - every phase carries its method inline so it runs standalone, asking the user questions at every decision point and recording results in the project docs/ folder (PERFORMANCE.md, ARCHITECTURE.md, ARCHITECTURE-OPTIMIZATION-PLAN.md) so the journey resumes across sessions. Use when the user wants to make an app faster, untangle drifted boundaries, fix slow endpoints and queries, or says 'it works but it is slow and getting worse'. For an untested prototype, improve-code-quality; for an aged codebase you fear to touch, remove-technical-debt; for greenfield structure, design-code-architecture; for marketing-site page speed, improve-website. For one framework in isolation, invoke that skill directly.

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Designs a coordinated multi-channel campaign or product launch around one story — objective, message, channel sequencing, timeline, assets, and the checklist that gets it out the door. Use this to plan a launch or campaign, sequence a go-to-market push, pressure-test a campaign before committing budget, or turn a product change into a coordinated set of activity. For ongoing channel programs rather than a bounded push, use `marketing-planning`.

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Refines broad, vague, or aspirational biomedical research objectives into clear, bounded, measurable, executable, and downstream-ready study objective statements. Always use this skill when a user has a general aim such as “explore a mechanism,” “study prognosis,” “investigate biomarkers,” or “look at treatment response,” but the objective is still too broad, non-operational, or too ambiguous to support protocol framing, design selection, analysis planning, or hypothesis design. Never assume that polished wording alone means the objective is actionable. Focus first on objective type, missing operational elements, scope discipline, and downstream-ready formulation.

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Clarifies a vague clinical or biomedical research idea into a structured, bounded, searchable, researchable, and testable question. Always use this skill whenever a user has an early-stage clinical or research thought, an over-broad topic, an ill-defined evidence question, or an unclear problem statement that must be translated into a question framing suitable for literature retrieval, evidence synthesis, gap analysis, study design, or downstream protocol planning. Never jump straight to answering the substantive medical question unless the user explicitly asks for that. Focus first on question framing, boundary setting, and downstream-ready formulation.

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Compare and implement eviction policies (LRU, LFU, FIFO, S3FIFO, ARC) for bounded-capacity caches. Use when choosing or implementing an eviction policy for a buffer pool, page cache, CDN edge, or LLM KV cache, or when writing a replay simulator that supports multiple policies. Clarifies recency vs frequency semantics, queue topology, saturating counters, ghost buffers, and the second-chance rule that distinguishes modern FIFO-family policies from classic LRU.

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。