215 件 ・ 関連度順
概要と使いどころ
Orchestrate the full ToolUniverse self-improvement cycle: discover APIs, create tools, test with researcher personas, fix issues, optimize skills, and push via git. References and dispatches to all other devtu skills. Use when asked to: run the self-improvement loop, do a debug/test round, expand tool coverage, improve tool quality, or evolve ToolUniverse.
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。
Automatically discover life science APIs online, create ToolUniverse tools, validate them, and prepare integration PRs. Performs gap analysis to identify missing tool categories, web searches for APIs, automated tool creation using devtu-create-tool patterns, validation with devtu-fix-tool, and git workflow management. Use when expanding ToolUniverse coverage, adding new API integrations, or systematically discovering scientific resources.
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。
Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.
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。
Repository-specific AGENTS.md authoring and maintenance workflow. Use when creating, refreshing, or expanding AGENTS.md coverage for a codebase, including deciding whether nested AGENTS.md files are needed for subsystems with distinct rules, workflows, or AI-sensitive 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。
Use this skill when the user asks about ARIA, ARIA roles, ARIA attributes, aria-label, aria-labelledby, aria-describedby, aria-expanded, aria-hidden, aria-live, aria-required, aria-invalid, "WAI-ARIA", "ARIA Authoring Practices", "APG pattern", "accessible name", "accessible description", live regions, custom widgets, dialogs, menus, tabs, accordions, comboboxes, tooltips, tree views, carousels, or is building any custom interactive component that requires ARIA roles and keyboard behavior beyond native HTML elements.
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。
Model gene-family birth-death dynamics across a species tree using CAFE5 (Mendes et al 2020 Bioinformatics 36:5516 gamma-distributed rate categories), CAFE5-error (annotation-error-aware), Count (Csurös 2010 ancestral state reconstruction), BadiRate (Librado 2012 likelihood + parsimony), DupliPHY-Family, and ALE/AleRax (for per-family DTL; see [[gene-tree-species-tree-reconciliation]]). Test lineage-specific gene-family expansions and contractions, distinguish biological dynamics from annotation artifacts, account for assembly fragmentation, identify functional enrichment in expanded / contracted families. Use when correlating gene-family changes with phenotype evolution, ranking lineages by adaptive gene-family-rate shifts, post-WGD dosage-balance analysis, or building Birth-death models from OrthoFinder presence/absence matrices.
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。
Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.
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。
Targeted deep research to fill a specific gap in an existing thesis. Use when user says "deepen", "flesh out", "expand on", "fill in", or specifies a thesis section to improve. Also supports --sync-metrics mode — detects stale financial metrics across every in-scope analytical section of a thesis (not just Key Metrics or Summary) and coherently updates every sentence that depends on them, using a Key-Metrics-table / FMP / web-search waterfall. Use when user says "sync metrics", "update the numbers throughout the note", or "fix stale figures across the whole thesis". The batch form `--sync-metrics --all-flagged` syncs every thesis flagged by the latest `/numbers --all-open` in one operation — detection fanned out to capped READ-ONLY agents, one consolidated confirmation gate, direct sequential writes (agents never write).
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。
Targeted deep research to fill a specific gap in an existing thesis. Use when user says "deepen", "flesh out", "expand on", "fill in", or specifies a thesis section to improve. Also supports --sync-metrics mode — detects stale financial metrics across every in-scope analytical section of a thesis (not just Key Metrics or Summary) and coherently updates every sentence that depends on them, using a Key-Metrics-table / FMP / web-search waterfall. Use when user says "sync metrics", "update the numbers throughout the note", or "fix stale figures across the whole thesis". The batch form `--sync-metrics --all-flagged` syncs every thesis flagged by the latest `$numbers --all-open` in one operation — detection fanned out to capped READ-ONLY agents, one consolidated confirmation gate, direct sequential writes (agents never write).
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。
Produce a traceable risk-based QA strategy without executing tests or expanding authorization.
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 well-structured, comprehensive Claude skills with clear activation criteria, detailed descriptions, usage examples, and proper documentation following best practices. Use when documenting new workflows, creating reusable skill patterns, establishing coding standards as skills, building team knowledge base, or expanding the skills library with new capabilities.
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 asked to review a plan, challenge a proposal, run a CEO review, poke holes in an approach, think bigger about scope, or decide whether to expand or reduce the plan.
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。
Model gene-family birth-death dynamics across a species tree using CAFE5 (Mendes et al 2020 Bioinformatics 36:5516 gamma-distributed rate categories), CAFE5-error (annotation-error-aware), Count (Csurös 2010 ancestral state reconstruction), BadiRate (Librado 2012 likelihood + parsimony), DupliPHY-Family, and ALE/AleRax (for per-family DTL; see [[gene-tree-species-tree-reconciliation]]). Test lineage-specific gene-family expansions and contractions, distinguish biological dynamics from annotation artifacts, account for assembly fragmentation, identify functional enrichment in expanded / contracted families. Use when correlating gene-family changes with phenotype evolution, ranking lineages by adaptive gene-family-rate shifts, post-WGD dosage-balance analysis, or building Birth-death models from OrthoFinder presence/absence matrices.
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。
Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.
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 a Coval accent testing report from runs across different speaker accents. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, STT/confirmation adjustments, accent-robust routing, or expanded accent coverage.
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 a Coval adversarial / red-team testing report and turn it into an agent-hardening plan. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or a per-scenario scorecard from an adversarial sweep and wants evidence-backed next steps such as prompt/guardrail changes, refusal hardening, verification fixes, escalation routing, or expanded attack coverage.
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 a Coval audio-quality testing report from runs across different voice, speaking-style, volume, interruption, and background-noise scenarios. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, tool handling fixes, STT/TTS adjustments, trace setup, or expanded audio-scenario coverage.
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。
Discovery batch that grows the Provider Access Launch queue. Use when asked to find more user-connected OAuth, API, API-key, remote MCP, marketplace, or partner-access campaigns for a capability, provider family, MCP/plugin catalog, or competitive gap. NOT for client Local Listings distribution.
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。
Sizing tokens for compact sidebars, nav panels, and menu lists. Use when building or refactoring a sidebar, settings menu, category list, filter bar, or expandable nav tree, or when a sidebar looks too wide, too padded, or wastes space.
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 vague Acceptance Criteria into measurable checks and test assertions
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 and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.
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 decompression bomb vulnerabilities where compressed input can expand to exhaust memory, targeting buffer-based decompression without size limits.
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。
The intelligence layer of Jury-rig. Decomposes natural language tasks into proposed Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, proposes wave and revision contracts, and expands nodes only when evidence supports a revised graph. Use for 'orchestrate', 'execute DAG', 'parallel agents', 'decompose task', 'coordinate skills'. NOT for single-skill tasks or simple linear 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。