القائمة
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/nastorehub/NasDoor --skill aiq-researchيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Generate images, video, and audio with ComfyUI — install, launch, manage nodes/models, run workflows with parameter injection. Uses the official comfy-cli for lifecycle and direct REST/WebSocket API for execution.
Pixel art w/ era palettes (NES, Game Boy, PICO-8).
Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).
استنادا إلى تصنيف SOC المهني
عرض SKILL.md
| name | aiq-research |
| description | Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend. |
| license | Apache-2.0 |
| permissions | {"env":["AIQ_SERVER_URL"],"network":["http://localhost:8000"]} |
| compatibility | Designed for Claude Code, OpenCode, Codex, and Agent Skills-compatible tools. Requires Python 3.11+ and network access to a running local AI-Q Blueprint server at `http://localhost:8000` by default. Non-local backends must be explicitly trusted by the user and granted by the host tool outside this public skill. |
| metadata | {"version":"2.1.0","author":"NVIDIA AI-Q Blueprint Team <aiq-blueprint@nvidia.com>","github-url":"https://github.com/NVIDIA-AI-Blueprints/aiq","tags":["nvidia","aiq","blueprint","deep-research","research-agents","agent-skills"],"languages":["python","bash"],"domain":"research-agents"} |
| allowed-tools | Read Bash |
Use this skill to call a locally running NVIDIA AI-Q Blueprint server through the helper script at
scripts/aiq.py.
Use this skill for research-shaped requests, including:
Do not use this skill for install, deploy, start, stop, UI, CLI, Docker, Helm, or troubleshooting requests. Those
belong to aiq-deploy.
Users need:
python3.AIQ_SERVER_URL set when the backend is not running at http://localhost:8000; non-local values must be trusted by
the user before any query is sent.The helper script has no third-party Python package dependencies; it uses Python standard-library HTTP modules.
health before sending research requests.aiq-deploy.Use AIQ_SERVER_URL when set. Otherwise try the default local backend:
python3 $SKILL_DIR/scripts/aiq.py health
Expected output: JSON from a reachable AI-Q health endpoint.
If health fails and no explicit AIQ_SERVER_URL was set, ask:
I do not see a reachable local AI-Q backend. Do you already have an AI-Q backend URL you want to use, or should I deploy a local Skill backend?
AIQ_SERVER_URL for subsequent helper calls and rerun health.aiq-deploy and preserve the original research request.401 or 403, stop and explain that this public skill does not manage
authentication. Ask the user to use an authenticated AI-Q skill or configure authentication for their environment.health succeeds but /chat or /v1/jobs/async/agents fails, report that the backend is reachable but not
compatible with this public research flow, then offer to run aiq-deploy validation.Before sending the request, state the resolved endpoint:
I will send this query to <AIQ_SERVER_URL>. Make sure this endpoint is trusted before sending sensitive information.
Do not send credentials, cookies, bearer tokens, or secret values through the query text.
Run:
python3 $SKILL_DIR/scripts/aiq.py chat "<USER_QUESTION>"
Expected output:
{"status": "deep_research_running", "job_id": "<JOB_ID>"} for asynchronous deep
research.If the response is normal JSON, present the result immediately. Do not force polling when there is no job_id.
If the response includes deep_research_running, extract the job_id and poll with the same absolute script path:
python3 $SKILL_DIR/scripts/aiq.py research_poll <JOB_ID>
Expected output: the final report JSON when the job completes successfully.
Use the runtime's non-blocking or background execution mechanism when available. If the chosen execution method requires escalated permissions, request explicit user approval first and explain why. Tell the user that deep research is running in the background.
If polling is interrupted, the job continues server-side. Resume with:
python3 $SKILL_DIR/scripts/aiq.py status <JOB_ID>
python3 $SKILL_DIR/scripts/aiq.py report <JOB_ID>
python3 $SKILL_DIR/scripts/aiq.py research_poll <JOB_ID>
Use status to inspect job status and saved artifacts. Use report when the job has already finished and you only need
the final output. Use research_poll to keep waiting for completion.
When research_poll completes successfully, fetch and present the full report. Keep citations and source URLs intact.
If the job status is failed, failure, or cancelled, show the error from the status response and ask whether the
user wants to retry with a narrower query or different approach.
IMPORTANT: This skill is designed for NVIDIA AI-Q Blueprint version 2.1.0.
Semantic Versioning Compatibility Rules:
Skill version: X.Y.Z
Blueprint or endpoint version: A.B.C
Compatible IF:
1. A == X (Major versions MUST match)
2. B >= Y (Minor version must be equal or greater)
3. C can be anything (Patch version does not affect compatibility)
Examples:
If your Blueprint version is not compatible:
| Script | Purpose | Arguments |
|---|---|---|
scripts/aiq.py health | Check whether the configured server responds | none |
scripts/aiq.py chat | POST /chat; may return inline output or a deep-research job ID | <query> |
scripts/aiq.py agents | List available async agent types | none |
scripts/aiq.py submit | Submit an explicit async job | <query> [agent_type] |
scripts/aiq.py research | Submit an async job, poll, and print the final report JSON | <query> [agent_type] |
scripts/aiq.py research_poll | Resume polling an existing async job | <job_id> |
scripts/aiq.py status | Fetch job status plus /state artifacts | <job_id> |
scripts/aiq.py state | Fetch event-store artifacts only | <job_id> |
scripts/aiq.py report | Fetch the final report for a completed job | <job_id> |
scripts/aiq.py stream | Stream SSE events from a job | <job_id> |
scripts/aiq.py cancel | Cancel a running job | <job_id> |
When the host supports a run_script() helper, call it with scripts/aiq.py and the arguments above. Otherwise, run
the equivalent shell command, such as python3 $SKILL_DIR/scripts/aiq.py health.
| Variable | Required | Default | Description |
|---|---|---|---|
AIQ_SERVER_URL | No | http://localhost:8000 | Local or self-hosted AI-Q server base URL |
AIQ_SERVER_URL.AIQ_SERVER_URL. Confirm the endpoint is trusted before sending
sensitive or confidential information.AIQ_SERVER_URL endpoints may log prompts, responses, and metadata.python3 $SKILL_DIR/scripts/aiq.py health
python3 $SKILL_DIR/scripts/aiq.py chat "Compare local AIQ deep research with a standard web search workflow"
Expected output:
<health JSON from AI-Q>
<JSON chat response or {"status": "deep_research_running", "job_id": "<JOB_ID>"}>
If AI-Q returns a job ID, continue with research_poll.
python3 $SKILL_DIR/scripts/aiq.py status <JOB_ID>
python3 $SKILL_DIR/scripts/aiq.py research_poll <JOB_ID>
Replace <JOB_ID> with the UUID returned by AI-Q. Expected output: status JSON followed by the report JSON when the
job completes. If the job failed, show the returned status and do not retry automatically.
| Topic | Documentation |
|---|---|
| Helper script | scripts/aiq.py |
| Deployment and backend validation | ../aiq-deploy/SKILL.md |
Symptoms:
health fails with connection refused.http://localhost:8000 URL does not respond.Causes:
Solutions:
export AIQ_SERVER_URL="http://localhost:<PORT>"
python3 $SKILL_DIR/scripts/aiq.py health
aiq-deploy and preserve the original research request.Symptoms:
/chat or async job calls.Causes:
Solutions:
health and the original query only after the authentication boundary is resolved.Symptoms:
health returns successfully./chat, /v1/jobs/async/agents, or polling commands fail.Causes:
Solutions:
python3 $SKILL_DIR/scripts/aiq.py agents
aiq-deploy validation.Symptoms:
running.running, but a report is returned or cancel says the job is already success.Causes:
Solutions:
python3 $SKILL_DIR/scripts/aiq.py status <JOB_ID>
has_report: true or job_status.status: success, fetch the report:
python3 $SKILL_DIR/scripts/aiq.py report <JOB_ID>
python3 $SKILL_DIR/scripts/aiq.py research_poll <JOB_ID>