「rank」の検索結果

Guides CLIP-as-service client, server, and CLIP search workflows for text/image embeddings, cross-modal ranking, and retrieval services.

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 ColBERT/colbert-ai for late-interaction retrieval: prepare data, inspect configs, train/fine-tune, index collections, search rankings, update indexes, serve search, evaluate MS MARCO/LoTTE outputs, or reason about Baleen multi-hop retrieval.

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。

Route BEIR repository tasks for benchmark data loading, retrieval evaluation, reranking, generation, and training workflows.

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。

Ranked next offensive moves from engagement state. Reads state/loot/Killchain, runs the deterministic analyzer, elaborates the top move. Use when asked "what next", "where to focus", "prioritize", or at the start of an engagement session.

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。

On-demand senior red-team lead advisor. Call at a decision point or obstacle to get wiki-grounded direction instead of hammering blindly. Dispatches a fresh RTL subagent that reads the engagement state + evidence + wiki and returns ranked directions with an explicit STOP. Use for "redteamlead", "RTL", "I'm stuck", "where do I go", "what next", "which vector", "should I keep hammering this".

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。

Vulnerability-research loop toward a novel CVE. Target triage -> attack-surface map -> ranked hypotheses -> investigate (RE / fuzz / audit) -> a finding deepens the loop, a dead-end pivots to a new approach. Uses the full wiki + hunt skillset. Scaffolds and persists state under raw/research/<project>/. Triggers - "research", "find a cve", "analyze this binary/library", "audit this code for vulns".

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 polishing, diagnosing, tailoring, or exporting resumes for LLM, RAG, Agent, Agentic RL, post-training, pretraining, AIGC, search/ranking, multimodal, AI backend, or LLM algorithm internships from raw resume text, a materials folder, and/or a target job description. Audits evidence, maps JD fit, enforces truth boundaries, writes polished and targeted resumes, generates interviewer-style grilling questions, answer cards, evidence-upgrade plans, and optional open-source project recommendations without fabricating experience.

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 "[Competitor] alternative" and comparison pages for developer tools. Build honest, high-converting comparison content that ranks for competitive search terms.

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 and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.

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 original short videos using the 界面恶作剧实体化｜屏内内容、屏外清除与手写回执 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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 used when analyzing recent market-moving news events and their impact on equity markets and commodities. Use this skill when the user requests analysis of major financial news from the past 10 days, wants to understand market reactions to monetary policy decisions (FOMC, ECB, BOJ), needs assessment of geopolitical events' impact on commodities, or requires comprehensive review of earnings announcements from mega-cap stocks. The skill automatically collects news using WebSearch/WebFetch tools and produces impact-ranked analysis reports. All analysis thinking and output are conducted in English.

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 ranking backlogs, deciding what to do first based on effort vs impact (quick wins vs big bets), prioritizing feature roadmaps, triaging bugs or technical debt, allocating resources across initiatives, identifying low-hanging fruit, evaluating strategic options with 2x2 matrix, or when user mentions prioritization, quick wins, effort-impact matrix, high-impact low-effort, big bets, or asks "what should we do first?".

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。

Options Strategy Advisor — analyzes implied volatility, IV rank/percentile, expected moves, put/call ratios, max pain, unusual activity, and recommends specific options strategies with risk/reward profiles based on the trader's directional outlook.

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。

Sector Rotation & Analysis — analyzes sector momentum rankings, money flows, economic cycle positioning, relative strength, top stocks per sector, valuations, and rotation signals to identify where institutional capital is moving.

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。

Code intelligence over repositories Guaardvark has indexed: semantic code search, exact-text search, file listing, PageRank repository map, import dependency graph, reading one class or function, analysis and generated rewrites, plus the System Mapper and self-improvement status. Use when the user asks where something is implemented, how modules depend on each other, or wants an architecture map of an indexed 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。

Analyzes test suites and suggests optimal test execution order based on code change impact and project requirements. Use when optimizing CI/CD pipelines, deciding which tests to run before committing, or selecting critical tests under time constraints. Prioritizes tests by analyzing recently modified files, test dependencies, and coverage overlap. Outputs detailed rankings with priority scores and reasoning to help teams run the most impactful tests first.

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 proof states in Isabelle or Coq and suggest applicable tactics to make progress. Use when users need help with: (1) Choosing the next tactic in an interactive proof, (2) Understanding what tactics apply to their current goal, (3) Getting unstuck in a proof, (4) Learning which tactics work for specific goal structures (conjunctions, implications, induction, etc.). Provides 3-5 ranked tactic suggestions with explanations for intermediate-level proofs in both Isabelle/Isar and Coq.

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。

Detect and analyze areas with high maintenance cost, poor design, or accumulated technical debt. Use this skill when reviewing codebases for quality issues, planning refactoring efforts, conducting code audits, assessing project health, identifying maintenance hotspots, or prioritizing technical improvements. Analyzes code smells, architectural issues, dependency problems, test quality, documentation gaps, and provides actionable recommendations with priority rankings.

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。

Locate root causes of failing regression tests by analyzing code changes, error messages, and test dependencies. Use when regression tests start failing after code changes, investigating test failures in CI/CD, debugging flaky tests, or understanding why previously passing tests now fail. Analyzes git diffs, stack traces, test output, and dependency changes to produce structured markdown reports ranking likely causes. Triggers when users ask to find why tests are failing, debug regression failures, investigate test breakage, or analyze failing test suites.

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 prioritized CVE watchlists and actionable security recommendations for repositories. Use when analyzing CVE scan results, creating security reports, prioritizing vulnerability remediation, or generating security gate reports for CI/CD. Takes CVE scan results (JSON/SARIF from npm audit, pip-audit, Snyk), reachability analysis, and cutoff date as input. Combines severity, reachability, exploitability, and dependency criticality to rank CVEs by practical risk. Outputs markdown reports with concrete next-step guidance (immediate upgrade, monitor, ignore with justification, apply mitigation) suitable for issue trackers, security reviews, and CI security gates.

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。

Identify the precise location of bugs in source code, modules, and systems. Use this skill when debugging applications, investigating test failures, analyzing error reports, tracing runtime issues, or performing root cause analysis. Analyzes stack traces, error messages, failing tests, and code patterns to pinpoint buggy functions, classes, files, or modules with confidence rankings and supporting 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。

Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.

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。

Full ICP-to-leads pipeline. Describe your ideal customer in plain English and get a ranked table of enriched decision-maker leads with emails and phone numbers.

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 and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.

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。