「baseline」の検索結果

Monitor competitors over time: baseline sites, pricing and ads by script, flag changes. "track our competitors over time"

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。

Score ad creative fatigue against baseline, predict days left, brief refreshes. "are our ads fatiguing"

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 the user has changed a prompt (system prompt, RAG template, agent instruction, etc.) and wants to know whether the candidate is better or worse than the baseline. Also use when the user mentions prompt A/B testing, prompt comparison, prompt optimization validation, "did my prompt change help," or prompt regression testing. Outputs per-dimension win rates with statistical significance using OpenJudge PairwiseAnalyzer.

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。

Scope management for legal matters — baseline capture, in-flight change control, OOS documentation, and scope retrospective. Use when asked to review scoping assumptions, assess whether work is in or out of scope, draft a scope change notice, track scope changes, prepare an OOS justification, run an OOS report, prepare a scope call agenda, or review what changed on a matter. Trigger on: 'scope change', 'out of scope', 'OOS', 'scope creep', 'is this in scope', 'the client wants us to also', 'additional work', 'scope review', 'what changed from the original scope', 'we need to revisit the quote', 'the budget assumed', 'OOS report', 'scope call with the client', 'run a scope 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。

Matter scoping across the full pre-execution arc — organise client data into a structured brief, capture the agreed baseline, or reconstruct scope mid-flight. Use when making sense of client information before a proposal, scoping a new matter, running a kickoff, defining scope, mapping stakeholders, or inheriting a matter mid-flight. Trigger on: 'make sense of this', 'structure this for the proposal', 'scope this matter', 'new matter', 'kickoff', 'what are we doing', 'who are the stakeholders', 'what does success look like', 'matter setup', 'intake', 'I've inherited this matter', 'organise this client data'.

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。

Expert guidance for FedRAMP certification and compliance under CR26 (FedRAMP Consolidated Rules for 2026). Use this skill whenever a user asks about FedRAMP authorization, ATO (Authority to Operate), cloud security for federal government, NIST SP 800-53 controls, CSP compliance, or any of the core FedRAMP document types: SSP, SAP, SAR, POA&M, CIS/CRM workbooks. Also trigger for questions about FedRAMP Certification Classes (A, B, C, D — new baseline labels: A = pilot/transitional, B = LI-SaaS/Low, C = Moderate, D = High, per NTC-0004), FedRAMP 20x (now the primary authorization pathway), OSCAL mandate (September 2026), 3PAO assessments, continuous monitoring (ConMon), gap assessments, system boundary definition, or architecture reviews for federal cloud. FedRAMP Ready retires July 28, 2026. When in doubt, use this skill — it covers the full FedRAMP lifecycle from readiness through continuous monitoring.

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。

Enforce complexity and size limits on Swift code with SwiftLint threshold rules — cyclomatic complexity, function/type/file length, parameter count — adopted via a violations baseline so existing code never blocks. Use when agent-written code needs deterministic size 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。

Gate test coverage with a ratchet — a committed baseline that coverage may never drop below and only ever rises. Ships a coverage-gate script (xccov-based) plus an advisory CRAP report (complexity × uncovered). Use when agent-written code needs a deterministic "tests were actually written" check.

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。

MsCoreUtils defines low-level functions for mass spectrometry data and is independent of any high-level data structures. These functions include mass spectra processing functions (noise estimation, smoothing, binning, baseline estimation),

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。

Expert knowledge for Azure Osconfig development including troubleshooting, security, configuration, and integrations & coding patterns. Use when running OSConfig via IoT for commands/networking, SSH Posture Control, agent health, or Windows security baselines, and other Azure Osconfig related development tasks. Not for Azure Update Manager (use azure-update-manager), Azure Automation (use azure-automation), Azure Policy (use azure-policy).

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。

Expert knowledge for Azure Policy development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when authoring JSON policies, deploying via ARM/Bicep/Terraform, enforcing security baselines, automating with Gatekeeper, or running policy-as-code in CI/CD, and other Azure Policy related development tasks. Not for Azure Blueprints (use azure-blueprints), Azure Role-based access control (use azure-rbac), Azure Resource Manager (use azure-resource-manager), Azure Security (use azure-security).

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。

Expert knowledge for Azure Attestation development including troubleshooting, best practices, security, configuration, and deployment. Use when validating attestation tokens, authoring policies, enforcing SGX/TPM baselines, or configuring private endpoints, and other Azure Attestation related development tasks. Not for Azure Confidential Computing (use azure-confidential-computing), Azure Virtual Enclaves (use azure-virtual-enclaves), Azure Dedicated HSM (use azure-dedicated-hsm), Azure Key Vault (use azure-key-vault).

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 guidance for writing and benchmarking optimized CUDA kernels for NVIDIA GPUs (H100, A100, T4) targeting HuggingFace diffusers and transformers libraries. Kernels must be kernel-builder/ABI3-compliant: no pybind11, no setup.py, TORCH_LIBRARY_EXPAND bindings only. Supports models like LTX-Video, Stable Diffusion, LLaMA, Mistral, and Qwen. Includes integration with HuggingFace Kernels Hub (get_kernel) for loading pre-compiled kernels. Includes benchmarking scripts to compare kernel performance against baseline implementations.

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 a user gives or references a webpage URL and wants to extract, reproduce, port, or locally replay a WebGL, WebGPU, Canvas, shader-like, animated background, interactive 3D, or web visual effect. Locks the target rendering surface group, records shader/resource/render graph/timing/input evidence, builds an evidence-matched local baseline, then projectizes it. Do not use for ordinary DOM/CSS page cloning.

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 a repeatable eval loop that grades agent output with an LLM judge, so prompt/skill changes get scored against a baseline instead of eyeballed. Reuses loopkit's verifier subagent as the grader — do not build a new one.

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。

RED-GREEN-REFACTOR for process documentation - baseline without skill, write addressing failures, iterate closing loopholes

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。

Plan, triage, and write academic rebuttals and review responses. Use when an AI research agent needs to handle conference, journal, workshop, or grant reviews; classify reviewer concerns; decide what evidence or experiments can change the decision; write an AC-facing executive summary; draft per-reviewer responses; correct factual misunderstandings without sounding hostile; handle novelty, baseline, method, experiment, clarity, and scope objections; or produce a final rebuttal checklist.

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。

JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes

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。

DELIVER wave orchestration workflow -- 9 phases from baseline to finalization. Load when user invokes *deliver command. Covers state tracking, smart skip logic, retry, resume, and quality gate enforcement.

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。

Weekly, heavy browser lane, read only toward the world with no exception. Works the surfaces on its own watchlist through one contiguous browser phase, captures one dated observation per real change with a verbatim quote and the exact URL, refuses to report any change against a surface it has no baseline for, and writes one capped weekly page. It types nothing that changes anything, takes no action on LinkedIn ever, sends only where you released the channel, spends only where you released it, and never touches a credential.

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 a GSD update, when local modifications were backed up to gsd-local-patches/ and must be merged back. Three-way compares the pristine baseline, the backup, and the new install, flagging conflicts instead of skipping files.

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。

Discover help documentation work from operately git history. Use when the user asks to audit what needs documenting since a release, tag, or SHA, or to identify documentation gaps from code changes. Requires a baseline SHA or tag as input.

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。

Creates project technical rules and recurring local procedures from the actual stack; edits guidance only, not architecture targets or application code.

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。

Defines measurable architecture drivers and constraints before system design; edits architecture docs only.

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。