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cccskills

「discipline」の検索結果

531 件 ・ 関連度順

概要と使いどころ

Cost discipline for recurring /loop runs: cache-aware pacing, event-driven-over-polling, no-change short-circuit, compact state handle, stop condition.

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。

Green-PT/honey-for-devs3242026年9月7日 更新

Transform an AI agent into a disciplined software development partner with strong judgment, transparent decisions, proportionate verification, and craftsmanship. Use for software implementation, feature work, bug fixing, refactoring, optimization, migrations, and sustained collaboration inside a codebase. Do not use merely because a task involves an AI agent; use a dedicated agent-design skill when the primary problem is agent architecture.

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。

shareAI-lab/lab-skills3152026年9月16日 更新

Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.

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。

lingxling/awesome-skills-cn3062026年10月7日 更新

Use when starting any Blender asset task, planning a production pipeline, coordinating multiple disciplines, or matching a reference photo/concept art. Invoke for game-ready assets, hard surface, environment, character, creature, export, or any multi-skill Blender workflow.

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。

arjun988/blender-skills2962026年7月11日 更新

Use when Codex feels slow, bloated, or heavy after heavy use. Provides safe session hygiene, archive strategy, and handoff discipline to keep daily Codex usage responsive and low-friction. Always pairs with comprehensive handoffs before archiving active work.

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。

majiayu000/spellbook2872026年10月8日 更新

tdd

無料

Write code through a disciplined, BDD-framed Test-Driven Development loop: build a behavior test list, then drive each behavior through red-green-refactor with an enforced observed-failure gate. Use when the user wants to implement, build, or write code test-first, "do TDD", follow "red-green-refactor", drive code from tests, choose the next test by the Transformation Priority Premise (TPP) or ZOMBIES ordering, or grow a feature behavior-by-behavior with tests leading. This skill writes and changes code; it does not produce a test plan document (use automated-test-planning, or manual-test-planning for a plan a person runs by hand), review or audit existing code (use code-review), restructure existing code outside a TDD loop (use refactor, or plan-a-change to plan a multi-module restructure), specify what a feature should do (use plan-a-feature), or find the root cause of a bug (use investigate). Runs its loop to completion without pausing for review; to review each behavior as it lands, use pairing.

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。

testdouble/han2832026年10月1日 更新

Use when an agent is asked to draft, rewrite, edit, review, polish, copyedit, simplify, humanize, or create written prose, including creative writing, essays, posts, scripts, speeches, emails, documentation, product copy, and other style-sensitive text. Apply George Orwell's six rules and ASD-STE100 Simplified Technical English as a plain-English discipline while preserving the user's intended meaning, audience, tone, and explicit constraints.

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。

tamdogood/builder-essential-skills2222026年8月17日 更新

Apply a disciplined engineering workflow to any code change. Use whenever implementing a feature, fixing a bug, or refactoring — before writing code, not after. Walks orient → baseline → smallest change → test → verify → self-review, and enforces language-agnostic hard gates (don't mass-reformat, keep the linter and type-checker clean, keep the build and tests green, make interface changes additive, protect security invariants).

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。

tamdogood/builder-essential-skills2222026年8月17日 更新

go

無料

Idiomatic Go - package and interface design, error wrapping, table-driven tests, generics, the modern standard library (slices/maps/cmp/errors.Join), current syntax, and logging discipline. Use when writing, reviewing, or refactoring any Go code, especially code drifting toward Java/Spring shapes (deep layer trees, generic repositories, heavy frameworks) - even if the user never says "idiomatic". Distilled from spf13/go-skills and adapted to this repo.

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。

inference-gateway/inference-gateway2152026年10月13日 更新

Trading as a business, performance review process, trade journaling, capital allocation discipline, business infrastructure for traders, KPI tracking for trading operations

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。

agentii-ai/agentii-investment-intelligence2072026年9月29日 更新

Medicines pipeline analysis over structured universes: Phase I-III assets with probability-of-success discipline (unadjusted peak x POS = modeled value; POS changes logged with reasons), trial status-diff tracking, and mechanism/competitor mapping via drug-knowledge lookups.

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。

agentii-ai/agentii-investment-intelligence2072026年9月29日 更新

Weekly product-level commercial tracking — TRx/NRx with current/4-wk/12-wk share and YoY, launch curves overlaid with same-class analogs plus a consensus-implied trajectory, LOE/biosimilar erosion series, GTN/net-price stress brackets, and per-row data-caveat discipline. Use to track any launched drug, biologic, device, or vaccine against its class and consensus.

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。

agentii-ai/agentii-investment-intelligence2072026年9月29日 更新

Weekly clinical-trial status diff — the 11-category change report over the stored weekly snapshots (spec 055 FR-B03). Surfaces exactly what changed on the trial registry for your coverage: New / Suspended / Withdrawn / Terminated / Recruiting / Recruitment-Complete / Completed / Ahead / Delayed / Upsized / Downsized, every row carrying previous and new values, with risk flags on Terminated and Downsized and re-timing flags on Ahead and Delayed. The stored-previous-value discipline makes each week's diff reproducible.

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。

agentii-ai/agentii-investment-intelligence2072026年9月29日 更新

Think and work like an expert Mammalogist. Use when a task calls for Mammalogist judgment. Reasons from mammalian life history and detectability-limited sampling through ASM MDD taxonomy, Sherman/camera-trap/SCR survey design, occupancy and SECR models, bat acoustic validation, and museum voucher discipline while treating trap heterogeneity, camera autocorrelation, closure violation, and WNS decontamination gaps 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

logician

無料

Think and work like an expert Logician. Use when a task calls for Logician judgment. Reasons from syntax-versus-semantics and object-versus-metalanguage discipline, the ⊢/⊨ distinction, and matching each logic to its intended semantics through natural deduction and sequent calculus (cut-elimination, subformula property), compactness and Löwenheim–Skolem, forcing and diagonalization, and proof assistants (Lean 4/mathlib, Coq, Isabelle/HOL, Agda) with Z3/CVC5/Vampire/Mace4 automation while treating use–mention conflation, second-order misuse of compactness, mis-stated incompleteness hypotheses (ω-consistency vs consistency), and Gödel philosophical overreach 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Ichthyologist. Use when a task calls for Ichthyologist judgment. Reasons from meristic fin formulae, sagittal otolith annuli/daily increments, larval flexion staging, and ICZN type discipline through Eschmeyer's Catalog, FishBase/WoRMS, MiFish/12S eDNA with blank controls, FSA/TropFishR/SS3 stock assessment, and Darwin Core museum metadata while treating CPUE catchability, unvalidated otolith ages, larval pigmentation loss, and eDNA false positives 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Gravitational-Wave Astronomer. Use when a task calls for Gravitational-Wave Astronomer judgment. Reasons like a senior GW astronomer across LIGO–Virgo–KAGRA matched-filter CBC searches, calibration-aware PE, GraceDB/GWTC alert–catalog discipline, BAYESTAR/Bilby skymaps, and EM follow-up campaigns.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Embedded Systems Engineer. Use when a task calls for Embedded Systems Engineer judgment. Reasons from hardware timing, interrupt latency, memory maps, and deterministic WCET resource bounds through DWT CYCCNT and Saleae logic-analyzer timing proofs, SWD/JTAG (J-Link/OpenOCD) with CFSR/HFSR/BFAR fault decode, FreeRTOS/Zephyr respecting configMAX_SYSCALL_INTERRUPT_PRIORITY, MISRA C:2012 and ISO 26262 ASIL discipline, Nordic PPK2 power profiling, and MCUboot signed OTA while treating priority inversion, Cortex-M7 uncached-DMA D-cache incoherence, CAN bus-off, I2C NACK storms, and brownout-during-flash-write NVS corruption 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Finite Element Analyst. Use when a task calls for Finite Element Analyst judgment. Reasons from discretization error, element technology, and constraint physics; runs mesh convergence and Richardson studies, Nastran/Abaqus/ANSYS workflows, RBE2/RBE3 and contact discipline, and ASME V&V 10 verification-before-validation reporting on governing QoIs.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Computer Architecture Researcher. Use when a task calls for Computer Architecture Researcher judgment. Reasons from ISA semantics, AMAT/CPI, MESI coherence, and branch prediction through gem5/SPEC/MLPerf evaluation, Amdahl and roofline discipline, TPU/GPU dataflow accelerators, DVFS/EDP, and Spectre/Meltdown mitigation overhead at ISCA/MICRO/HPCA rigor.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Data Scientist. Use when a task calls for Data Scientist judgment. Reasons from CRISP-DM business estimands, leakage-safe sklearn Pipelines and nested CV, SQL/warehouse semantic metrics, A/B power and SRM/AA guardrails, causal DAG covariate discipline, and Model Cards/Datasheets while treating train-test leakage, Simpson's paradox, peeking, and PSI>0.25 drift 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Clinical Microbiologist. Use when a task calls for Clinical Microbiologist judgment. Reasons from blood-culture volume and contamination criteria, staged Gram–ID–AST reporting, MALDI-TOF/VITEK/Phoenix and EUCAST RAST, CLSI M100 vs EUCAST breakpoint discipline, WHONET antibiograms, and NHSN MDRO alerts—treating contaminant vs pathogen and VME/ME 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Astrodynamicist. Use when a task calls for Astrodynamicist judgment. Reasons from two-body plus perturbation force models through Cowell/Encke propagation, batch LS and EKF orbit determination, SPICE/Horizons ephemerides, CCSDS OEM/CDM exchanges, and TEME–GCRF frame discipline while treating drag, stale TLE/B*, and covariance frame mismatch 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Astronomer. Use when a task calls for Astronomer judgment. Reasons like a senior observational astronomer from the telescope and catalog outward — Landolt/Stetson photometry, Gaia/MPC astrometry, Horizons ephemerides, SDSS–ZTF–Rubin survey discipline, TOPCAT cross-matches, and calibrated detection vs upper-limit reporting.

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。

K-Dense-AI/scientific-agents2052026年10月3日 更新