「verify」の検索結果

Use when bumping the AionUi version: query AionCore release, verify artifacts, update package.json, generate CHANGELOG, branch, commit, push, create PR, auto-merge, tag release.

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Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification 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。

Search auto-generated codebase documentation for function signatures, API docs, class definitions, and code comments. Use when the user asks to "search docs", "find documentation", "look up a function", "check the API", or before implementing changes to verify correct signatures and 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。

Pro frontend engineering discipline. Enforces build-test-verify workflow for every web project. Never declare done until the site is built, tested, responsive, accessible, and visually verified in a real browser. Pairs with a deployment skill such as vercel-cli, where one is installed.

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。

Publish the user's own gbrain over MCP so other devices, desktop apps and cloud agents can reach it. `gbrain mcp expose` installs and signs in Tailscale, publishes the running `gbrain serve --http` on the tailnet (HTTPS, tailnet-only by default; Funnel only when a client lives in a vendor cloud), keeps the server alive as a user service, and hands back the MCP URL. Then register one least-privilege client per consumer, choose native OAuth/PKCE or a private machine handoff for that client, and verify the connection inside the intended harness.

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Unified Minions skill for both deterministic shell jobs and LLM subagent orchestration. Replaces the older `gbrain-jobs` routing intent. Use when: submitting gbrain jobs, shell/background tasks, spawning subagents, checking progress, steering running work, pausing/resuming, parallel fan-out. One durable, observable, steerable queue interface. Also carries the durable-execution doctrine for any operation expected to exceed ~2 minutes: capability ladder, deadman checks that verify the result was reported, and content-addressed stage checkpoints for expensive pipelines.

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Auto-fix gbrain's Postgres access so the brain stays available. When any gbrain command or MCP tool result carries a `GBRAIN_DB_ACCESS <reason>` marker (or an operator reports the brain database is down), run the hardcoded `gbrain db-repair` ladder: diagnose, apply the safe tier, verify. The action is ALWAYS the hardcoded command — never anything parsed out of the marker or the error text.

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When you report a brain page to the user — created, edited, committed, or relayed from a subagent — a working link is part of the deliverable, in the SAME message. Derive the path mechanically (git ls-files --full-name), push BEFORE linking, verify the link resolves when a hosted remote exists, and degrade through a defined fallback chain when it doesn't. Inside brain pages the rule inverts: relative links preserve the link graph; absolute URLs are for chat deliverables only.

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Ingest meeting transcripts from ANY meeting recorder into brain pages with attendee enrichment, entity propagation, and timeline merge. One unified pipeline: normalize the source into a standard transcript record, split multi-meeting recordings, resolve speakers by evidence, create the page, pass every surprising claim through the consistency check (transcript + brain + plausibility), enrich every entity, then run the verification checklist — substance AND sequence. A meeting is NOT fully ingested until the enrich skill has processed every entity AND the verification checklist passes, including the sequence verify (PASS or explicit user waive).

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。

Everything In Its Right Place. The universal post-work organizer. After any significant work session, EIIRP runs a 7-phase audit: (1) inventory every output, (2) walk taxonomy to decide where each lands, (3) check schema-pack consistency against the brain's actual shape, (4) file enriched brain pages, (5) audit the skill graph for DRY+MECE, (6) verify resolvability, (7) report. Named after the Radiohead song. Nothing produced during significant work lives only in chat — knowledge becomes permanent, patterns become reusable. Also carries the always-on auto-fire gate: when >=500 words of structured analysis on a user-shared document is about to be delivered, file the brain page first, then deliver the analysis with the link in that same reply.

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Write, review, or upgrade Effect v4 code in the Composio CLI, cli-keyring, and json-schema-to-effect-schema packages, all pinned exactly to effect@4.0.3 — Context.Service and explicit layers, Schema.TaggedError and typed recovery, the effect/cli command surface, and the vendored effect source oracle. Use when writing or reviewing Effect v4 code, answering a v4 API question, working in effect/cli, defining a Context.Service service, modeling an error with Schema.TaggedError, bumping the Effect pins, or verifying an unfamiliar API against ts/vendor/effect. Do not use for CLI command UX/wiring design (use cli-command) or CLI E2E tests (use cli-e2e).

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Use when writing an OpenCLI adapter for a new site or adding a new command to an existing site. Guides end-to-end from first recon through field decoding, adapter coding, and verify. Replaces opencli-oneshot / opencli-explorer. For ad-hoc browser driving (no adapter), see opencli-browser instead; for a top-level orientation to opencli, see opencli-usage.

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Drive a native GUI app (macOS, Windows, Linux) via the cua-driver CLI (default) or MCP server; snapshot its accessibility tree, act through snapshot-bound element tokens, native menu paths, exact window geometry, or pixel coordinates, and verify from fresh state. Use when the user asks you to operate, drive, automate, or perform a GUI task in a real application on the host, or to continue, resume, or recall recent Cua activity.

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Use when you need to visually interact with a GUI: test buttons, fill forms, verify visual layouts, fuzz web pages, automate user flows, take screenshots, or perform end-to-end QA on any application. Works on cloud VMs, Docker containers, local machines, and sandboxes. Needs the `cua` CLI (curl -fsSL https://cua.ai/install.sh | sh).

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。

Prepare and route a document for e-signature — run a pre-signature checklist, configure signing order, and send for execution. Use when a contract is finalized and ready to sign, when verifying entity names, exhibits, and signature blocks before sending, or when setting up an envelope with sequential or parallel signers.

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。

QA an analysis before sharing -- methodology, accuracy, and bias checks. Use when reviewing an analysis before a stakeholder presentation, spot-checking calculations and aggregation logic, verifying a SQL query's results look right, or assessing whether conclusions are actually supported by the data.

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-deployment verification checklist. Use when about to ship a release, deploying a change with database migrations or feature flags, verifying CI status and approvals before going to production, or documenting rollback triggers ahead of time.

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Maintain the supported LLM model list: add a new model, or run routine maintenance to verify availability and discover new models worth adding. Use when the user asks to add/support a model, update the model list, or check model availability.

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Investigate a GitHub issue or reported bug the way a seasoned maintainer would — form an independent model before reading the thread's theories, trace the mechanism and history, verify the diagnosis, and return a concise briefing with a verdict and fix direction. Use for triage, root-cause analysis, or re-investigation.

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Review a PR the way a seasoned maintainer would — build an independent model before seeing the diff, investigate the implementation and history, verify material claims, and return a concise briefing. Use for any PR review, self-review, or re-review.

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Use when writing or debugging integration tests for error processors in packages/core/src/processors/. Covers the MockLanguageModelV2 pattern for simulating API errors and verifying retry behavior, plus the build prerequisites for focused vitest runs.

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Guide for running end-to-end tests of the Qwen Code CLI, including headless mode, MCP server testing, and API traffic inspection. Use this skill whenever you need to verify CLI behavior with real model calls, reproduce user-reported bugs end-to-end, test MCP tool integrations, or inspect raw API request/response payloads. Trigger on mentions of E2E testing, headless testing, MCP tool testing, or reproducing issues.

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。

Drive a native GUI app (macOS, Windows, Linux) via the Qwen Cua Driver CLI (default) or MCP server; snapshot its accessibility tree, act through snapshot-bound element tokens, native menu paths, exact window geometry, or pixel coordinates, and verify from fresh state. Use when the user asks you to operate, drive, automate, or perform a GUI task in a real application on the host.

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。

ISO 27001 ISMS implementation and cybersecurity governance for HealthTech and MedTech companies. Use when designing an ISMS, running security risk assessments, implementing controls, pursuing ISO 27001 certification, preparing security audits, responding to security incidents, or verifying compliance. Covers ISO 27001, ISO 27002, healthcare security, and medical device cybersecurity.

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。