「ida」の検索結果

Runs the payroll-confidence chain end to end — forecasts cash across the payroll window with cash-flow-snapshot, ranks and drafts overdue-invoice reminders with invoice-chase to close any gap, then assembles timesheets, flags every anomaly, and stages the run with payroll-prep. On Gusto the run is staged for the owner to submit; on QuickBooks Payroll, or with no payroll system, the last step is a validated run sheet the owner keys in. This chain never presses the payroll button. Builds on the ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books), with Gmail or M365, PayPal, Square, Stripe, and either Gusto or QuickBooks Payroll adding detail, and falls back to CSV and timesheet uploads. Use it whenever payroll is the worry, including "can I make payroll," "payroll is due Friday," "plan payroll," "will I have enough to pay the crew," or "I need to run payroll but money is tight." Accepts optional horizon and payroll-date arguments.

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。

Takes a pile of applications and turns it into a ranked shortlist, scored only against the job's stated rubric, with drafted replies to every candidate, scheduled interviews, and an onboarding checklist for whoever gets hired. Picks up where job-post-builder leaves off and carries the funnel through to first day, including the payroll setup handoff. Runs on Gmail and Google Calendar, deepens with Gusto, DocuSign, and Drive or M365, and works entirely from uploaded resumes with drafted replies the owner sends by hand. Use this whenever the owner has applicants to deal with — including phrasings like "I've got 40 resumes and no time," "who should I interview," "screen these applications," "help me narrow this down," "set up interviews for the top three," or "I need to tell the rest no." Reach for it when the owner mentions applicants, resumes, candidates, or being buried in a hiring inbox.

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 an offer letter with comp details and terms. Use when a candidate is ready for an offer, assembling a total comp package (base, equity, signing bonus), writing the offer letter text itself, or prepping negotiation guidance for the hiring manager.

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。

Track and manage recruiting pipeline stages. Trigger with "recruiting update", "candidate pipeline", "how many candidates", "hiring status", or when the user discusses sourcing, screening, interviewing, or extending offers.

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。

Autonomous, report-only documentation review for Mastra docs. Use when auditing changed docs against source, validating contextual code examples or API coverage, checking canonical mastra-docs guidance, or running narrow deterministic 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。

Design guidance for charts, graphs, dashboards, maps, and data visualizations, including a local palette validator.

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 auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:memory-review or asks what has been learned and what should be promoted or pruned.

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, test, and score the quality of skills within the claude-skills ecosystem. Comprehensive meta-skill: structure validation, Python script testing (syntax + imports + runtime + output format), multi-dimensional quality scoring with letter grades and tier classification (BASIC/STANDARD/POWERFUL). Use when authoring a new skill, auditing existing skills for tier promotion, setting up pre-commit hooks for skill quality, or integrating skill QA into CI.

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 the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts. Covers eval-driven prompt iteration, RAG metrics (relevance, faithfulness, coverage), agent workflow validation, and token/cost budgeting — all model-agnostic, with three stdlib Python tools.

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。

Phase 1 of building a Claude Managed Agent — interview the founder about the one job the agent should do, then produce a build sheet (CMA primitives table + v1/v2 deferrals + eval plan) WITHOUT needing their API key yet. Use when the user says "help me scope an agent", "I have an idea for an agent", "what should this agent be", or when the orchestrator routes phase=interview. Drives the six intake slots (job, trigger, inputs, actions, definition-of-done, recurrence) via AskUserQuestion, maps them to primitives with interview_planner.py, assembles build-sheet.json with build_sheet_builder.py, and validates limits with primitives_validator.py. Connectors are mockable in v0 (schema-true custom tools); real MCP servers become v1 deferrals. Distinct from stage-launch (which turns the sheet into 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。

Phase 4 of building a Claude Managed Agent — make it run without you. Turn a graded agent into a recurring scheduled deployment (POSIX-cron), an event-driven curl trigger, or confirmed on-demand use, then finalize the versioned roadmap. Use when the user says "run it every morning", "put it on a schedule", "nightly", "weekly", "automate this", "make it recurring", or when the orchestrator routes phase=run-without-you. deployment_builder.py builds the POST /v1/deployments payload (initial_events must include user.message; optionally nests a user.define_outcome so each firing self-grades); cron_validator.py validates the 5-field cron + IANA timezone and prints the wall-clock DST note; next_directions_writer.py writes NEXT-DIRECTIONS.md. No tool makes API calls — the deployment is created via BYOK curl. Distinct from grade-iterate (the in-session loop) and wrap-up (closeout).

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。

Phase 2 of building a Claude Managed Agent — turn a validated build sheet into exact API payloads and a resumable BYOK curl launch script, then launch (environment → agent → session → kickoff) using the founder's OWN Anthropic key. Use when the user says "launch it", "deploy the agent", "create the agent now", or when the orchestrator routes phase=stage-launch. payload_generator.py emits the four ordered payloads; launch_script_writer.py writes launch.sh that reads $ANTHROPIC_API_KEY at runtime and never embeds it; payload_validator.py runs a pre-launch check including an API-key-leak scan. No tool in this skill makes network calls — the user runs launch.sh themselves. Distinct from interview (planning) and grade-iterate (the outcome loop).

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 experiments to test assumptions for an existing product — prototypes, A/B tests, spikes, and other low-effort validation methods. Use when validating assumptions, testing feature ideas cheaply, or planning product experiments.

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 lean startup experiments (pretotypes) for a new product. Creates XYZ hypotheses and suggests low-effort validation methods like landing pages, explainer videos, and pre-orders. Use when validating a new product idea, creating pretotypes, or testing market demand.

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 the release, check the released binaries, is 0.18.x safe to roll out, prove a published desktop release. Boots the RELEASED mac-arm64 enterprise and cloud binaries through the packaged journeys, checks updater manifests and notarization, and publishes 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。

Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, organizing workflows into folders, managing credentials, auditing instance security, or using any n8n-mcp tool. Provides tool selection guidance, parameter formats, and common patterns. IMPORTANT — Always consult this skill before calling any n8n-mcp tool — it prevents common mistakes like wrong nodeType formats, incorrect parameter structures, and inefficient tool usage. If the user mentions n8n, workflows, nodes, or automation and you have n8n MCP tools available, use this skill 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。

Discovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.

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。

Guides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads. Don't use for simple text-based chat applications or workloads without real-time streaming requirements.

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。

Google platform decision and setup guidance, loaded on demand from Google's skill catalog. Use when a developer is choosing or setting up part of their stack, such as where to run a service, a database, storage, messaging, authentication, analytics, ads, or AI model serving, and a Google product is a reasonable candidate - whether or not a vendor is named - or when a request names a Google product or API. Brings in the matching Google skill so the answer can weigh Google options, their trade-offs, and when they are not the right fit. Skip when the stack is already settled on another provider and no Google product is named, or the task involves no platform choice.

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。

Provides guidance for authoring Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers environment context discovery, Airflow 2 vs 3 compatibility, authoring best practices, and local/remote validation processes. Use when creating or extending an Airflow DAG. Don't use when authoring Python code unrelated to Airflow DAGs.

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。

Author, validate, test, and deploy YARA-L 2.0 detection rules and evaluate end-to-end detection coverage gaps in Google SecOps. Use when writing new detection rules, tuning existing rules, validating syntax, testing logic against historical telemetry, or evaluating detection coverage against threat intelligence blogs, CVE disclosures, and Threat Detection Opportunities (TDOs) using synthetic UDM events and long-running coverage analysis. Don't use for alert triage (use secops-triage), deep forensic event reconstruction on infected hosts (use secops-investigate), or case management operations (use secops-cases).

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。

Review Apache ShardingSphere or user-authorized downstream pull requests and PR discussions from public or authorized repository evidence. Use for code-correctness or mergeability decisions, CI-focused review, root-cause and regression analysis, complete consolidated findings, copy-ready committer feedback, challenged findings, multi-round review, and formal review of local implementation candidates in the repository completion loop.

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。

URDF robot description authoring and validation. Use when creating, editing, inspecting, validating, or debugging `.urdf` files, robot links, joints, limits, inertials, visual/collision geometry, mesh references, frame conventions, or robot-description artifacts. Use the SRDF skill for MoveIt2 semantic groups and IK/path-planning semantics; use the CAD skill for STEP/STL/3MF/DXF/GLB outputs. Open and visually review existing URDF files in CAD Viewer.

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。

MoveIt2 SRDF authoring, validation, and planning-semantics workflow. Use when creating, editing, inspecting, or validating `.srdf` files, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-paired planning semantics, or SRDF handoff for live review. Use the URDF skill for robot structure and the SDF skill for simulator descriptions. Open and visually review existing SRDF files in CAD Viewer.

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。