「fid」の検索結果

Multi-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.

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。

Pattern extraction, confidence-scored evaluation, skill creation, organization, versioning, and cross-project export pipeline.

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。

Multi-dimensional code assessment across security, quality, performance, and maintainability with confidence-gated reporting (>=80%) and Router Contract generation.

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。

This skill should be considered when you need to normalize testing engineers' written defect reasons following the provided product codebooks. This skill will correct the typos, misused abbreviations, ambiguous descriptions, mixed Chinese-English text or misleading text and provide explanations. This skill will do segmentation, semantic matching, confidence calibration and station validation.

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。

Estimate heart rate (HR) and breathing rate (BR) in bpm from a cleaned 1-D physiological time series such as radar phase, WiFi CSI amplitude, PPG, or a chest-motion signal. Use when Claude needs to choose HR/BR bandpass edges, pick a peak frequency from a noisy band, reject the HR second harmonic that often dominates the fundamental, handle respiration-harmonic leakage into the HR band on slow breathers, or flag low-confidence estimates. Not for arrhythmia / beat-to-beat analysis, multi-subject source separation, or rapidly non-stationary rates.

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。

Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.

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。

Move an idea up the fidelity ladder (content-first → wireframe → low-fi → high-fi → code) with a validation plan at each level, plus user-journey mapping and usability-testing scripts. Use when the user wants to prototype, wireframe, map a user flow, or plan/run usability testing.

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 game or app from a description so that a live screenshot matches a generated rendering. Use when the user says "dream loop" or asks for something built to a very high level of graphical fidelity.

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。

Turn an incoming set of findings — from an AI reviewer, a referee report, a code review, a linter, or a second model — into verified fixes, without letting a confident misread damage correct work. Every finding is a CANDIDATE until checked against the actual source. Use whenever you receive review comments, audit findings, or a critique you did not write yourself, especially when the reviewer is a model or when the volume is too large to check by feel.

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。

Pre-screen analysis outputs (tables, figures, logs) built on restricted or confidential data for statistical-disclosure-limitation problems before any release. Scans for small cell counts, complementary-suppression gaps, dominance (p-percent / (n,k)), re-identifiable exact counts, PII leakage, and unrounded sensitive statistics; classifies each finding CRITICAL / WARNING / OK and gates on any CRITICAL. Use before depositing or sharing restricted-data results, or when the user says "disclosure check", "SDL scan", "is this output safe to release", "check for small cells", "disclosure avoidance", "pre-screen for the RDC", or "can I export this from the enclave".

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。

Assemble a submission-ready replication package to the AEA Data and Code Availability Standard (DCAS) / openICPSR / Social Science Reproduction Platform expectations — standard replication README, dataset manifest, computational-requirements capture, a Table/Figure → script:line map, and a confidential-data deposit plan. Use when user says "build the replication package", "prepare the openICPSR deposit", "make the AEA data and code package", "DCAS compliance", "assemble the deposit for the journal", or after a paper is accepted and the journal's data editor needs the package. NOT a numeric verifier — it calls /audit-reproducibility to confirm claims reproduce before packaging.

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。

Draft a funder-compliant Data Management Plan (NSF DMP, NIH DMS Policy 2023, ERC, Horizon Europe) by composing the confidential-data and environment-capture primitives. Sections cover data description, formats/metadata, storage/backup, access/sharing, preservation/archiving, and roles. Use when user says "data management plan", "DMP", "DMSP", "NIH data sharing plan", "write the data plan for my grant", or when a grant proposal needs a data-management section. NOT a submission tool — produces a draft the user pastes into the funder portal (DMPTool, NIH ASSIST, Horizon Europe portal).

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。

Extract anonymized frame-by-frame body and hand trajectories from an authorized reference video, with skeleton previews, confidence evidence, and machine-readable keypoints. Use when the user asks to 提取博主动作, 提取人体动作轨迹, 做姿态参考, 生成骨架视频, or prepare motion control data for an avatar; do not route graphic-animation replication here.

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 under time pressure when the situation is still changing and you must act before certainty — cycle Observe→Orient→Decide→Act on ~70% confidence, then re-observe.

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 Thinking coaching foundation knowledge: coach identity and philosophy, quality and fidelity constraints, method sequencing, coaching state schema, and the canonical deck 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。

Tests/benchmarks a third-party LLM endpoint (OpenAI- or Anthropic-compatible): availability, fidelity, speed, concurrency, protocol compliance, quality regression. Use before hand-rolling a curl loop, when onboarding a provider, or debugging "system prompt 不生效" / a tok/s claim — 测评/压测一个模型或渠道. Not for TTS/voice-clone supplier eval (use the audio skill).

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。

Extracts Feishu/Lark Docs, Wiki, Sheets, and Minutes (妙记) transcripts into faithful local Markdown via the lark-cli API — no LLM paraphrasing, browser-DOM fallback when lark-cli can't reach content. Use whenever the source is a Feishu/Lark URL and fidelity matters — 导出飞书文档/合集/妙记转写, 把飞书 wiki 转 markdown, or archiving a collection — even if the user just says "save this". Also covers owner-exported .docx → Markdown.

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。

Write a specific, non-generic cover letter that connects your evidence to the role. Use when asked to write a cover letter, an application letter, or a note to accompany a resume. Produces a tight 3–4 paragraph letter — a real hook, two evidence paragraphs mapping your proof to the job's needs, and a confident close — tailored to the company, ready to export as a designed PDF.

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。

Decode a mainland China labour contract (劳动合同) before signing: probation, pay and its structure, working hours, social insurance, non-compete and confidentiality, termination terms and anything that conflicts with the Labour Contract Law. Use when asked 帮我看看劳动合同, 劳动合同有什么坑, 试用期合法吗, 竞业限制条款, or review my Chinese employment contract. Produces a clause-by-clause decode with red, amber and green flags, the statutory limits each clause must respect, the questions to ask HR, and suggested wording for changes. Not legal advice.

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。

Assess physical and transition climate risk for a site, product, or portfolio with scenario-based structure. Use when asked to run a climate risk assessment, evaluate physical or transition risk, prepare TCFD/ESRS-style climate risk analysis, or assess how climate scenarios affect an asset or business. Produces a hazard-exposure-vulnerability matrix across 2030/2040/2050 horizons and labelled scenarios, with financial-impact ranges, confidence levels, and adaptation options.

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。

Extract pixel-level data from an image of a chart or graph and produce a structured data table. Use when asked to extract data from a chart image, transcribe numbers from a graph, digitise a chart, or turn a screenshot of data into a table. Produces a structured table with extracted values, confidence levels, and a reconstructed chart source. Best used with Claude Opus 4.7 or newer for reliable chart data extraction.

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。

Turn interview notes into a structured candidate scorecard and hire recommendation. Use when asked to write an interview scorecard, a candidate evaluation, an interview debrief, or to summarize feedback into a hire/no-hire call. Produces a per-competency assessment with evidence and ratings, an overall recommendation with confidence, and the open questions for the next round — evidence-based, bias-aware, and decision-ready.

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。

Extract every hidden assumption from a plan or document and put a price on each one — what it costs if wrong, what it costs to test. Use when about to commit to anything whose author says 'obviously' or whose spreadsheet has hardcoded cells: the bounty hunt makes the invisible load-bearing beliefs explicit and tells you which three to test this week. Produces the assumption ledger (priced and ranked), the cheapest test for each dangerous one, and the document's honest confidence statement.

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。

Extract and risk-rate hidden assumptions in a product brief or PRD. Use when asked to review a product brief for assumptions, audit a PRD for risks, find hidden assumptions, validate product plans, or run an assumption analysis. Produces a prioritised assumption map with confidence and impact scores, recommended validation methods, and critical assumption flags.

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。