「dating」の検索結果

Create, update, or validate a product brief. Use when the user wants help producing, editing, or validating a brief.

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。

Verify integrity of persisted state, skill outputs, and context bus data. Use when validating .rune/ files or sub-agent outputs against prompt injection, memory poisoning, identity spoofing, or adversarial payloads. Called by sentinel, team, session-bridge.

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 whenever the user wants to interact with Figshare - searching public datasets/articles, downloading Figshare files, listing their own articles/collections/projects, creating or updating articles, or uploading files (including large multi-part uploads) via the Figshare v2 REST API. Trigger on mentions of "figshare", figshare DOIs (10.6084/m9.figshare.*), figshare.com URLs, or phrases like "upload my dataset to figshare", "publish to figshare", "get figshare article".

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。

Releasing Craft CMS plugins — tagging, Packagist propagation, GitHub releases, branch promotion, shared-library ordering, history rewrites. ALWAYS load when cutting, preparing, verifying, or debugging a plugin release: bumping a version, dating a changelog, creating or moving a git tag, or checking what Packagist serves.

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。

Confirms or rejects findings from review-llm-artifacts before deletes or risky refactors. Loads review-verification-protocol-style checks per finding. Use after a review run, when the user wants to reduce false positives, before fix-llm-artifacts on dead code, or when validating a full-project scan.

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。

Documentation templates and standards: README structure, API reference format, changelog (Keep a Changelog), and comment guidelines. Use when creating or updating documentation. Loaded automatically by the doc-writer agent.

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。

Run GitHub Actions workflows locally with act on macOS. Use when validating workflow wiring or a job before pushing. Not for authoring the workflow itself (ci-workflow-authoring).

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。

Router for the ./taskctl portfolio-task lifecycle. Use when creating, updating, triaging, executing, reviewing, or closing RIPDPI tasks, backlog items, bugs, epics, or OpenSpec-backed work.

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-commit implementation analysis for Retail-Agentic-Commerce. Use before commits, after significant changes, or when validating Apps SDK tools, mock data, MCP communication, widget isolation, or implementation quality.

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。

Validate data quality in CSV/Excel files for vehicle insurance platform. Use when checking required fields, validating data formats, detecting quality issues, or generating quality reports. Mentions "validate", "check fields", "data quality", "missing values", or "quality score".

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。

Writes employee benefits guides explaining health insurance, retirement plans, PTO, and perks in plain language. Use when onboarding new hires or updating benefits documentation.

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。

API endpoint design and testing for vehicle insurance data platform. Use when designing new API endpoints, testing existing ones, validating response formats, or debugging API issues. Covers 11 core endpoints including 3 new pie chart distribution endpoints, parameter validation, error handling, and integration patterns.

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。

Amazon Bedrock Automated Reasoning for mathematical verification of AI responses against formal policy rules with up to 99% accuracy. Use when validating healthcare protocols, financial compliance, legal regulations, insurance policies, or any domain requiring deterministic verification of AI-generated 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。

Run Ultimate Bug Scanner (UBS) for code review. Use when reviewing code, checking for bugs, scanning for security issues, validating AI-generated code, or pre-commit quality checks.

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。

Improve a Hinge dating profile through research-backed screenshot audits, photo selection and ordering, conversational discovery, prompt and caption writing, settings review, or post-launch troubleshooting. Use for a full profile rebuild or a focused request about photos, copy, positioning, match quality, or profile performance.

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。

Manages a Zotero academic reference library through both the local API (localhost:23119, read-only) and the Web API (api.zotero.org, read-write), using a structured collection hierarchy (Inbox / Active Projects / Background / Reading Queue / Archive / Meta) plus project, status, priority, and type tags. Handles adding papers with full metadata, deduplication, attaching provenance notes, moving items between collections, updating tags after reading, listing the prioritized reading queue, and setting up the literature scaffold for a new project. Use when the user asks to add / save / file / organize a paper in Zotero, check / list / clean up the reading queue, move papers between collections, tag papers for a project, query their library ("what do I have on X?"), or set up Zotero for a new research project.

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。

Merges GitHub Pull Requests after validating pre-merge checklist. Use when user wants to merge PR, close PR, finalize PR, complete merge, approve and merge, or execute merge. Runs pre-merge validation (tests, lint, CI, comments), confirms with user, merges with proper format, handles post-merge cleanup.

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。

Security hygiene for GSD's self-modifying skill and agent system. Use this skill whenever: creating, editing, or deleting skill files (.claude/skills/, .claude/commands/), modifying agent definitions (.claude/agents/), working with YAML configuration or chipset files, handling JSONL observation data (.planning/patterns/), processing community-contributed skills or chipsets, any file path operations that could involve user input, or when installing/updating project-claude configuration. Also activates for discussions about skill-creator security, trust models, or content hygiene.

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 at write time to vector/embedding memory — Grove content-addressed insertion, chroma/pgvector upserts, memory-consolidation promoting session traces to MEMORY.md, or embedding externally-ingested content. Scores each candidate record against a fixed panel of sentinel queries and quarantines any record that would become the nearest neighbor of too many unrelated queries — a hub — whether from adversarial poisoning or accidental over-generality. This is the memory-record-side sibling of skill-injection-guardian (file-side) and the write-side complement of memory-use-warrant (read-side). Quarantine, never silently drop; a human reviews. Backed by the admission-time hubness gate (arxiv 2606.19692v1). Triggers on inserting into vector memory, consolidating memory, and embedding stranger 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。

Guidance for verifying documentation accuracy against running OpenStack infrastructure. Use when detecting documentation drift, validating operations procedures against live systems, or confirming that runbooks produce expected results on the deployed cloud. Implements NASA Product Verification (SP-6105 SS 5.3) applied to documentation artifacts.

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。

Load, validate, and use DACP bundles as structured execution context. Detects .bundle/ companion directories, validates integrity (manifest schema, fidelity, provenance), loads typed data, and builds ExecutionContext for receiving agents. Scripts are NEVER auto-executed. Use when processing incoming DACP bundles, interpreting .bundle/ directories alongside .msg files, validating bundle integrity, or building execution context from bundle payloads.

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 valid, consistently named Gherkin story files with correct IDs, timestamps, and tags. Use when writing or updating story 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。

Test and validate MaaFramework Pipeline JSON, recognition nodes, action nodes, CustomAction/CustomRecognition wiring, resource loading, and end-to-end task behavior. Use when running `run_pipeline`, checking OCR/TemplateMatch/ColorMatch ROI, validating `context.run_task()` results, auditing `action: Custom` or `recognition: Custom` registrations, or choosing the right resource-check command.

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。

Implement affective valence as directional derivative of interoceptive energy landscapes for AI alignment. Use when building alignment-aware RL agents, validating GF(3) conservation in reward signals, training Langevin-based policies, or analyzing fold-change detection signals in POMDP environments.

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。