'query run' 검색 결과

Work with a Grafana instance — search and read dashboards, run datasource queries (Prometheus, Loki, PostgreSQL, etc.), inspect alert rules and silences, post annotations, and manage folders. Use this whenever the user mentions a Grafana dashboard, panel, or alert; pastes a Grafana URL; asks "what does this dashboard show", "query this metric in Grafana", "is this alert firing", "silence this alert", or wants to create/export a dashboard — even if they don't say "API". Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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Investigate an alert, page, or production symptom in an incident channel or a team's oncall / monitoring channel, and report findings a human can verify. Ordinary conversation and chatter are not alerts; leave those alone. Use when an alert or page lands, when error rate, latency or saturation is up, when someone asks "why is X broken", "investigate", "what changed", "root cause this", pastes a monitor, dashboard, trace or error-tracker link, or reports production trouble; also by default when an alert lands in a covered channel unasked. Feed-level asks land here too ("which alerts matter", "triage today's alerts"), plus the scheduled alert-review routine and the ticket path ("customer X can't check out"). Runs a fast first pass posted as a short interim update with a TL;DR, every finding carrying the query or link to verify it, then proposes the fix and — with connector access and confirmation — carries it out, never unattended. Afterwards `incident-postmortem` writes it up.

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Uses AWS SDK CloudWatchClient GetMetricData and CloudWatch Logs Insights StartQueryExecution to automate incident triage. Correlates alarms via DescribeAlarms with X-Ray trace segments for root cause analysis.

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选择和实现状态管理方案时使用。覆盖 React (Redux Toolkit / Zustand / Jotai / Valtio / TanStack Query) / Vue (Pinia) / Angular (NgRx / Signals) / Svelte (Stores / Runes)。融合客户端状态 + 服务端状态分离。

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Cheminformatics toolkit for fine-grained molecular control. Parse and write SMILES, SDF, MOL and InChI; compute descriptors (MW, LogP, TPSA, QED, Bertz); build fingerprints (Morgan/ECFP, RDKit, MACCS, atom pair, torsion) and score Tanimoto, Dice or cosine similarity; run SMARTS substructure search and reaction SMARTS; generate 2D depictions and ETKDG 3D conformers; extract Murcko scaffolds and canonical hashes; control sanitization and stereochemistry directly. Also trigger on rdkit, Chem.MolFromSmiles, rdFingerprintGenerator, SDMolSupplier, SMARTS query, ETKDG, or FilterCatalog. For standard workflows with a simpler interface use the datamol skill, which wraps RDKit; use rdkit for advanced control, custom sanitization, and specialized algorithms.

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Use this skill when an external audit, attestation examination or assessment is coming and the team wants populations and evidence ready for the samples the auditor will pull, or asks "prepare for audit sampling", "what samples will the auditor ask for", "get our populations ready", "the auditor wants a list of all changes in the period", "evidence for the leavers sample", "Type II sample prep" or "how do we prove completeness of the population". Lists the populations an auditor is likely to sample, builds each from the system of record with the query that produced it, checks completeness and the evidence behind a dry-run sample, and writes a readiness file per population plus a list of gaps to fix before fieldwork.

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Testing React SPAs: React Testing Library + Vitest/Jest for components and hooks, msw for network mocks, Playwright/Cypress for e2e. Query priority, user events, async assertions, mocking patterns. Use this skill to: - Pick the right runner (Vitest vs Jest) and setup. - Write component tests with RTL using accessible queries. - Test custom hooks via renderHook. - Mock network with msw at the boundary. - Set up Playwright or Cypress for end-to-end coverage. Do NOT use this skill for: - General React conventions (see react-conventions). - State management testing patterns specific to a store lib (see react-state-management). - Form-specific testing (apply react-forms patterns inside test).

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Log a bias-log / vipassana observation to the memex store the moment a reasoning pattern surfaces, mid-session or at close. Use when you catch a bias in your own reasoning (anchoring, confirmation, trust-the-summary), when a pace tell or verification gap appears, or when meditate/observe produces a reflection worth persisting across sessions. Primary path pipes the body to `memex add` over stdin (`--title` required) then runs the `meditate-vipassana` extractor to make it queryable; secondary path appends a numbered bullet to `docs/OBSERVATIONS.md`.

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Entity and relation tracking skill using MCP memory server patterns and local knowledge graph storage. Build persistent knowledge graphs of entities, relationships, and observations across agent sessions. Covers the MCP memory server (@modelcontextprotocol/server-memory), local JSON-based graphs, and entity-relation querying patterns for long-running agents.

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Onboarding workflow for cross-library KB query in a consulting practice. Discovers existing user-scope library registrations, prompts for additions, validates each library, helps activate the relevant ones for the current project, runs a smoke test, and reports a clear "ready" or "issues to fix" verdict. Use --verify-only to skip prompting and just validate existing setup (sub-task 23 of

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Process unhandled Slack messages as Claudicle with persistent memory. Loads user models and soul state, posts terminal-styled thinking messages, generates cognitive-step responses, updates memory based on mentalQuery decisions. Requires Session Bridge listener running.

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Writes and reviews Swift App Intents code that exposes app actions and data to Siri, Shortcuts, Spotlight, widgets, Control Center, and Apple Intelligence. Use when adding AppIntent, AppEntity, OpenIntent, AppShortcutsProvider, EntityQuery, Focus Filters, AssistantEntity/AssistantIntent schemas, on-screen awareness, LongRunningIntent/CancellableIntent, EntityCollection, SyncableEntity, AppIntentsTesting, or when wiring SwiftData/networked data into intents.

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Perform actions in Linear (read, create, update, search issues, projects, comments, teams, cycles, labels, etc.) by writing and running small Node scripts against the official @linear/sdk TypeScript SDK with a personal API key. Use this when the user wants to do Linear work from the terminal without the Linear MCP server, or asks to list/open/create/update/close Linear issues, leave comments, or query teams, projects, users, or workflow states.

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Troubleshoot and resolve common issues with the ClickHouse Node.js client (@clickhouse/client). Use this skill whenever a user reports errors, unexpected behavior, or configuration questions involving the Node.js client specifically - including socket hang-up errors, Keep-Alive problems, stream handling issues, data type mismatches, read-only user restrictions, proxy/TLS setup problems, or long-running query timeouts. Trigger even when the user hasn't precisely named the issue; vague symptoms like "my inserts keep failing" or "connection drops randomly" in a Node.js context are strong signals to use this skill. Do NOT use for browser/Web client issues.

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Use when the user wants to run SQL - especially analytical SQL - on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB - embedded ClickHouse SQL in Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window functions, windowFunnel, geoToH3, JSON path ops, Session, parametrized queries); imports `chdb` or calls `chdb.query()`. SKIP this skill for pandas-style DataFrame method-chaining (use chdb-datastore instead) or ClickHouse server administration.

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Connect to and query ClickHouse (a local server or a ClickHouse Cloud service) from the terminal using the official clickhousectl CLI, including the browser OAuth login flow. Use when the user wants to run SQL against ClickHouse, explore schemas and tables, inspect Cloud services, or authenticate clickhousectl. For building a local dev environment or deploying to Cloud, defer to the official ClickHouse skills (see Scope).

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Perform actions in Linear (read, create, update, search issues, projects, comments, teams, cycles, labels, etc.) by writing and running small Node scripts against the official @linear/sdk TypeScript SDK with a personal API key. Use this when the user wants to do Linear work from the terminal without the Linear MCP server, or asks to list/open/create/update/close Linear issues, leave comments, or query teams, projects, users, or workflow states.

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Fix nodes silently disappearing from RFDB when an enricher or post-resolution pass writes new nodes via BatchHandle. Use when: (1) writing a TypeScript enricher that should ADD nodes/edges to existing files, (2) after calling `client.createBatch()` + `batch.addNode({file: 'X', ...})` + `batch.commit()` the original nodes in file X have vanished, (3) tests that load a graph fixture, run an enricher, then query original nodes get empty results, (4) a verification step shows expected nodes pre-enrichment but 0 post-enrichment. Root cause: `BatchHandle.commit()` invokes RFDB's `commit_batch` which AUTO-POPULATES `changed_files` from each added node's `file` field, then the server DELETES all existing nodes whose `file` matches before inserting new ones — file-level upsert semantics. This is correct for the JS/Haskell analyzers (which fully re-emit a file's contents) but catastrophic for enrichers that only ADD to existing files.

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Work with the @upstash/vector TypeScript/JavaScript SDK, a serverless vector database for embeddings, similarity search, semantic search, and RAG (retrieval-augmented generation). Use when upserting, querying, fetching, ranging, or deleting vectors, upserting raw text against an index with a built-in embedding model, choosing dense, sparse, or hybrid indexes, filtering by metadata, organizing data with namespaces, running resumable queries, or connecting Upstash Vector to an AI or LLM application. Also use when the user asks for a vector store, vector search, nearest-neighbor or kNN search, embeddings storage, semantic cache, recommendations or similarity features, or a hosted vector index that needs no infrastructure.

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OpenTSC v2.1: Soul/Shell architecture for interpersonal intelligence. Local, offline-first, with event graphs, judgment engine (K7), self-creation (K8), three-layer attributes, calibrated predictions, 11 VSM professions, and a pluggable zvec memory index (semantic search, identity resolution, jieba segmentation, emotion scoring incl. batched+cached LLM) that runs with zero extra deps. Transforms implicit social judgment into explicit, queryable, auditable, evolving intelligence.

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Interactively gather parameters for `python -m cli.inference.text_generate`, generate a concrete text generation simulation command, explain assumptions, ask for execution confirmation, then run the command and summarize performance metrics. Use when the user wants to validate a specific model, hardware profile, batch/query size, prefill or decode scenario, TP/DP/EP/MOE parallel strategy, profiling database, chrome trace, empirical metrics export, or a best row produced by throughput_optimizer.

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Use this skill when the user needs official desktop Obsidian CLI Bases or Bookmarks workflows, including base discovery, view/query operations, base item creation, and bookmark management. Keep this skill separate from general note CRUD, runtime admin, Sync/Publish, and devtools diagnostics.

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Query Strava fitness data including activities, athlete stats, segments, routes, clubs, and gear. Use when the user asks about cycling, running, swimming, workouts, training, or Strava data.

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Use when you need deep host + certificate reconnaissance for an IP or need to run a Censys search query. Returns services, TLS certificates, ASN, and location. Free tier is severely limited (250 queries/month) — use sparingly. Retrieval only.

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