'query run' 검색 결과

Query Codex banked reset credits from the local Codex Desktop login state and report available reset count plus expiration times. Use when the user asks to check Codex reset credits, reset opportunities, reset chances, reset count, rate-limit reset credits, or expiration times; also use when the user provides a codex-reset-credits-skill or codex-reset-credits runbook link and asks Codex to query the result directly.

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Run SQL against Amazon Redshift — submit statements, poll status, page through results, and browse databases/schemas/tables. Use this whenever the user wants to query Redshift (provisioned cluster or Serverless), ask "what tables are in this schema", check a query's status, or mentions `redshift-data`, a Redshift cluster identifier / workgroup name, or a `redshift-data.{region}.amazonaws.com` endpoint. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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Query, read, create, update, and describe Salesforce records — Accounts, Contacts, Opportunities, Leads, Cases, and custom objects. Use this whenever the user wants to look up a Salesforce record, run a SOQL query, update an Opportunity, check an object's fields, or asks "what's in Salesforce" — even if they don't say "API". Also use it for any URL under *.salesforce.com / *.lightning.force.com or a mention of a Salesforce record ID or SOQL. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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Query the ChEMBL database web services for measured bioactivity data, compound records and calculated properties, targets, assays, mechanisms of action, drug indications and warnings. Use this skill to build curated SAR or QSAR datasets for a target, look compounds up by SMILES, InChIKey, name, or ChEMBL id, run similarity and substructure searches, and check what chemistry is already known against a protein. Also trigger when a query mentions ChEMBL ids (CHEMBL...), pChEMBL values, IC50/Ki/Kd/EC50 retrieval, assay confidence scores, or ebi.ac.uk/chembl.

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How to use the Appwrite CLI well. Covers when to use appwrite.config.json vs `appwrite client`, pull/push vs one-shot service calls, type-safe SDK and model generation, query flags, CI auth, Cloud regional endpoints, function/site variables, and traps that `--help` will not mention. Does not catalog commands — run `appwrite <command> --help` for flags. Use whenever running `appwrite`, deploying or pulling functions/sites/tables, generating application code from a table schema, initializing or linking a project, scripting Appwrite, or when the user mentions the Appwrite CLI, appwrite.config.json, `appwrite generate`, `appwrite types`, or `appwrite client`.

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Multi-backend observability CLI for querying metrics, logs, and traces across 12 backends. This skill should be used when the user runs obz commands, constructs metric/log/trace queries, configures providers, parses obz JSON output, or troubleshoots obz errors. Covers all core commands (metric query/list/info/labels/label-values/series, log search, trace search/get), global flags, time formats, output modes, config files, and exit codes.

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Run SQL queries against psql, BigQuery, or MySQL from the terminal, including natural-language-to-SQL and schema exploration. Use when analyzing data, inspecting DB state, or debugging tables. Trigger on "query the database", "SQL", "show me data from", "explore table".

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Retrieve, query, and identify relevant Google Cloud Monitoring metric descriptors for a GCP service or resource (such as Compute Engine, Spanner, BigQuery, Cloud Run, Cloud SQL, Pub/Sub, Cloud Storage, etc.). Use when asked to find, list, search, or discover GCP metric types, names, kind/value schemas, or descriptors.

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Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for public Vertex AI deployments (use the `vertex-deploy` skill) or for running model evaluations (use the `agent-platform-eval-flywheel` skill).

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Query a user's Gemini Notebook (formerly NotebookLM) for source-grounded answers through a logged-in browser session on their Google account. Uses the account's usage limits and writes browser state. Runs only on an explicit request: /blog notebooklm, "ask my Gemini Notebook", "ask my NotebookLM notebook", or "query my notebook library". Also used by blog-write when the user named a notebook for research. Not for generic research or note-taking.

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Run natural-language data query workflows for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads reports.

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Preserve output from expensive one-shot commands for monitoring and later analysis. Use when rerunning a build, API query, CI inspection, or diagnostic would be costly and a managed background process is not the better interface.

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Comprehensive, measurement-driven performance optimization for latency, throughput, memory/GC, and tail behavior. Use when the user asks to optimize/speed up, reduce latency (p95/p99), increase throughput/QPS, lower CPU/memory/allocations/GC pauses, profile hot paths, or run a benchmarked perf pass (including JSONL/query-heavy code). Requires before/after measurement on a runnable workload (or an explicit `UNMEASURED` plan) plus a correctness gate.

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How to use the Appwrite CLI well. Covers when to use appwrite.config.json vs `appwrite client`, pull/push vs one-shot service calls, type-safe SDK and model generation, query flags, CI auth, Cloud regional endpoints, function/site variables, and traps that `--help` will not mention. Does not catalog commands — run `appwrite <command> --help` for flags. Use whenever running `appwrite`, deploying or pulling functions/sites/tables, generating application code from a table schema, initializing or linking a project, scripting Appwrite, or when the user mentions the Appwrite CLI, appwrite.config.json, `appwrite generate`, `appwrite types`, or `appwrite client`.

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Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries. Use when the user asks about GitHub issues, pull requests, workflows, or wants to interact with GitHub repositories from the command line — including tasks like check CI status, create PR, list issues, or query the GitHub API.

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Guides agents through creating and safely sizing a Replay Vision scanner: choosing the scanner type (monitor/classifier/scorer/summarizer), shaping the RecordingsQuery that selects sessions, and — crucially — estimating observation volume and checking the org's monthly quota before creating, so a broad scanner doesn't exhaust the budget on its first scheduled sweep. TRIGGER when: user asks to create, set up, or configure a Replay Vision scanner, OR when you are about to call vision-scanners-create, OR when widening an existing scanner's query or sampling_rate via vision-scanners-update. DO NOT TRIGGER when: only reading scanners or observations, deleting a scanner, or running an existing scanner against a single session on demand (vision-scanners-scan-session).

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Turborepo (高速モノレポビルドシステム) リファレンス。 turbo.json、turbo run、dependsOn、task tags、キャッシュ (local / remote)、 workspaces (pnpm / npm / yarn / bun / nub / aube)、Rust / Python / Go ワークスペース (実験的)、 --filter、turbo query affected、turbo prune、turbo gen、watch、parallel 実行、 Remote Cache (Vercel / 自前ホスト Remote Cache API)、devEngines.packageManager、 エラー診断 (recursive turbo invocations, missing root task, invalid env prefix)。

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Build, update, and query a persistent project knowledge graph from skills, memory, docs, and code structure — stdlib Python only, no external tools. Dual-mode: skill-library (agent-loom) or application (any consumer repo). Load when the user asks for a knowledge graph, project map, skill relationships, query the graph, update the graph, or trace how components connect. Auto-runs on memory-handoff and project-setup bootstrap. Also triggers on "build the graph", "what connects to X", "map this project".

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gget으로 유전자 정보와 염기·아미노산 서열을 조회하고, 유사 서열과 유전자 집합의 기능을 조사합니다. 결과와 검색 조건을 나중에 확인할 수 있는 연구 기록으로 남깁니다.

• 유전자 ID와 전사체 정보를 조회합니다
• 염기 및 아미노산 서열을 가져옵니다
• BLAST나 BLAT로 간단히 검색합니다

H100과 H200의 GPU 재고를 조회하고 고정 요금 견적 요청과 조달 현황을 확인합니다. 기기 인증 해제와 명시적으로 허가받은 노드 검증도 지원합니다.

• H100 및 H200 재고 확인
• 고정 요금 견적 요청
• 견적과 조달 진행 상황 확인

언어별 자료에 따라 Claude 앱을 구현하고 유지보수합니다. 공식 SDK 호출, 도구 연동, 모델 이전, 비용 검토와 평가 절차 마련을 다룹니다.

• 앱에 Claude API 연동
• 맞춤 도구를 쓰는 에이전트 구현
• 기존 Claude 연동의 모델 이전

Browse and search OmniRoute's AI model catalog from the command line. Filter by provider or capability, check model aliases, validate compatible models before adding them, and maintain manually registered model details.

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• Finding AI models by provider or capability
• Checking model aliases and name variants
• Validating a model before adding it