「sweep」の検索結果

Run a cumulative daily or retrospective sweep of research papers on a chosen topic, audit their claims, methods, integrity signals, and independent support, then identify overlooked but feasible project or business opportunities in a detailed source-grounded report. Use when asked to monitor papers every day, mine buried research, evaluate whether a paper is credible or reproducible, find unimplemented research ideas, or separate promising work from hype, weak evidence, and retracted or contradicted results.

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。

Think and work like an expert Microelectronics Engineer. Use when a task calls for Microelectronics Engineer judgment. Reasons from CTE mismatch, θja networks (JESD51), and package RLC through wire bond (Au–Al IMC, loop height), flip-chip (UBM, underfill, HIP/NWO), J-STD-020 MSL, and JESD22 TCT/uHAST; treats datasheet θja without board definition, wire sweep, die-attach voids, and soak-mode 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。

Think and work like an expert AI Researcher. Use when a task calls for AI Researcher judgment. Reasons from data generating processes, inductive biases, and compute-data-algorithm trade-offs through train/val/test discipline, seed sweeps, ablation ladders, and standards like NeurIPS reproducibility checklists, model cards, and lm-eval-harness, while treating data leakage (Kapoor & Narayanan taxonomy), benchmark contamination, spurious correlations, and reward-model overoptimization 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。

Turn any X (Twitter) profile into a 10.3s animated "POSTING LICENSE" card video — a fake driver's license in X's branding: the card slides in over an animated dot-matrix ground, license text types on letter-by-letter, follower / following / post counters tick up, a diagonal glimmer sweeps as the card tilts in 3D, it flips to a fine-print back with a signature write-on, then crouches and leaps out of frame. Trigger on: "X driver's license", "posting license", "make an X license for @handle", "license card video". The whole composition is a finished template — the agent only supplies profile data and renders.

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。

Resolve the currently-unresolved review threads on the current branch's PR in one sweep — assess each, fix it (test-first, verified) or reply-only, then reply and resolve — and return a summary. Use standalone to address PR review feedback, or as the thread-handling step invoked by /watch-pr. Repo is adamayoung/TMDb.

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 and maintain high-quality Swift DocC documentation for the TMDb package, following its established `///` conventions. Use when adding or changing any public declaration (protocol, class, struct, enum, actor, model, property, initializer, method, typealias) and when keeping the DocC catalog in sync. This is the single source of truth for the project's documentation style — applied inline as you write, and followed by the `documentation-writer` agent for bulk sweeps.

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。

Fix the currently-failing status checks on the current branch's PR in one sweep — route each failing check to the right diagnosis skill (via a Haiku subagent, escalating to Opus on a repeat failure), apply and verify the fix, commit, and push once — then return a summary. Use standalone when CI is red, or as the check-fixing step invoked by /watch-pr. Repo is adamayoung/TMDb.

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。

Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a reviewer.

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。

End-to-end substantive-integrity forensic sweep of a research paper (especially autoresearch / AI-Scientist-style output). Orchestrates the whole pipeline: ingest (arxiv-id | pdf | dir → working dir + pdftotext for L0) → /evidence-ledger (artifact manifest + observability level L0/L1/L2 + span-anchored claims.json) → fan out the integrity auditor skills (consistency, citation, baseline, experiment, presentation, proof-derivation, eval-design — each reads the ledger, emits span-anchored findings) + the zero-verdict-weight AIS writing-style track → advisory memos (/adversarial-case-builder + /novelty-duplication-advisory, no verdict weight) → deterministic tools/adjudicate_findings.py (--ledger REQUIRED) → reviewer-ready Integrity Forensics Report. Cross-model (fresh codex per dimension) and reviewer≠adjudicator: the model proposes findings, the deterministic adjudicator decides the verdict. Observability-aware, detect-only, never an opaque AI-text classifier (a separate zero-weight AIS section lists AI writing-style impressions, never moving the verdict). Triggers: "anti-autoresearch", "integrity audit this paper", "forensic review", "audit a submission", "审一篇投稿的诚信".

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。

Check that a document's claims about code are actually true by reading the prose, the code, and the tests and reporting (or fixing) where they disagree. Use whenever the user wants to verify a README, guide, spec, or docstring still matches the code; whenever they mention documentation drift, doc-code sync, "is this still accurate", stale docs, or keeping docs/tests/code consistent; before publishing or merging a docs change; or as a periodic doc-accuracy sweep. The agent reads the prose's meaning directly — there is no claim-comment DSL to maintain. Pairs with TDD — the test suite is the deterministic behavioral gate, this skill is the semantic prose-vs-reality review.

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。

Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint 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。

Analyze liquid markets with a strict ICT/SMC framework that combines multi-timeframe bias, liquidity sweeps, displacement, close-confirmed MSS/BOS, FVG/OB/Breaker/OTE retracements, premium-discount location, session timing, invalidation, targets, and risk-to-reward. Use for ICT chart reviews, live-market analysis, OHLCV scans, or validating a user's trade thesis. Return an auditable setup status and conditional plan; do not use for generic indicator analysis, order execution, or claims of proven institutional intent.

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。

Delegate coding, code review, analysis, and research jobs to Google Antigravity CLI (agy) sub-agents that run alongside your own work. Use this whenever the user asks to spin off, offload, or delegate a task to Antigravity, agy, Gemini, or an "external agent"; wants a second opinion or independent review from a different model; wants intensive repo work (audits, large refactors, research sweeps) run in the background while you keep working; or says things like "have Antigravity do it", "spin up a sub-agent for this", or "get more done in parallel". Also use it proactively when a task is a good fit for parallel delegation and the user has expressed a preference for using Antigravity workers.

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。

Detecting unnecessary files, unused code, and orphaned files, and proposing safe deletion. Not for removal execution (Builder), repo structure (Grove), or scope cutting (Void).

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。

When the user wants to edit, review, or improve existing marketing copy, or refresh outdated content. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' 'copy sweep,' 'tighten this up,' 'this reads awkwardly,' 'clean up this text,' 'too wordy,' 'sharpen the messaging,' 'refresh this content,' 'update this page,' 'this content is outdated,' or 'content audit.' Use this when the user already has copy and wants it improved or refreshed rather than rewritten from scratch. For writing new copy, see copywriting.

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。

Detects common LLM coding agent artifacts across four categories (tests, dead code, abstraction, style) over the project or changed files — using parallel subagents when the agent supports them, otherwise four sequential passes. Scans files changed since main by default; use --all for full-project scan. Triggers on LLM cruft cleanup, agent-generated code review, dead code sweeps, test-quality passes, or when the user asks to scan the whole 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。

Repo Updater - Multi-repo synchronization with AI-assisted review orchestration. Parallel sync, agent-sweep for dirty repos, ntm integration, git plumbing. 17K LOC Bash CLI.

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。

Generate MaaFramework Pipeline nodes and recognition snippets from screenshots or observed UI state. Use for OCR node generation, ROI sweep, choosing TemplateMatch/OCR/ColorMatch/CustomRecognition, preserving target-file schema style, and designing `next`/`[JumpBack]` links before merging generated nodes into pipeline JSON.

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。

Compressive Vasomotion Hypothesis (CVH) — vasomotion as a fast compression sweep that collapses ambivalent neural resonances (the Bayesian-blur problem) into a definite state. Use when modeling the ~100ms taṇhā 'grab', precision-weighting as compression forcefulness, or the generative collapse step of vasocomputational active inference.

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。

When the user wants to edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' 'copy sweep,' 'tighten this up,' 'this reads awkwardly,' 'clean up this text,' 'too wordy,' or 'sharpen the messaging.' Use this when the user already has copy and wants it improved rather than rewritten from scratch. For writing new copy, see copywriting.

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。

When the user wants to edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' or 'copy sweep.' This skill provides a systematic approach to editing marketing copy through multiple focused passes.

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。

Plans a research project as a decision map that persists across sessions, resolving one ticket per session until the design is defensible and pre-registerable. The map lives as Markdown in the repository, literature sweeps run as parallel research tickets, and the resolved map compiles into a pre-analysis plan. Use at project start, when a design has more open decisions than one conversation can hold, or when planning restarts each session. Not for executing analyses or writing the paper.

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。

Find the places in Anabasis where TypeSafe's Jev, a cheap calibrated System One classifier (Noul, Choice, Score over a text state), could replace or sit beside an LLM call, an embedding classifier, a prose regex, a lexical ranking or a blind-judge labelling loop, and prove each one in shadow against recorded labels before anything moves. Sweeps the tree for the five shapes, puts every candidate through the authority filter (what owns the decision, can it touch a pass, a score, a denominator or a gate) and the jev-1.13 fit filter, then writes a surface card with a runnable Bun experiment. Use when asked where Jev, TypeSafe or a System One model fits, what it could replace, or to run the autoresearch feature-discovery loop over this repository's records.

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。

Invoke whenever writing, changing, reviewing, or sweeping tests in Anabasis. A write-time gate for every new or changed test, and a read-first audit that prunes or consolidates tests re-asserting source, duplicating a stronger owner, coupling to implementation, or keeping a test-only export alive. Knows the suite's helpers, fakes, walls, rule-4 invariance tests and runner, and hands removal claims that rest on overlap to test-impact-and-consolidation.

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。