القائمة
Conduct deep research with multi-source search, evidence compilation, and structured report generation.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Control message formatting and writing style for Lark/Feishu conversations.
Create, query, edit, and manage Feishu Bitable (multidimensional spreadsheets) via lark-cli base — apps, tables, fields, records, views, dashboards, forms, workflows.
Manage Feishu calendar events via lark-cli — create/update/delete events, manage attendees, query free/busy and suggest available time slots, find and book meeting rooms.
List Feishu group chat members and resolve chat metadata via lark-cli.
Create a Feishu cloud document from Lark-flavored Markdown via lark-cli, with optional folder or wiki placement.
Comment management and media (image/file) operations on Feishu cloud documents via lark-cli.
| name | deep-research |
| description | Conduct deep research with multi-source search, evidence compilation, and structured report generation. |
| triggers | {"intent_patterns":["research|调研|调查|分析|analysis|market"],"tool_signals":["web_search","web_fetch"],"context_signals":{"keywords":["调研","研究","analysis","research"]},"confidence_threshold":0.6} |
| priority | 8 |
| exclusive_group | research |
| max_tokens | 200 |
| cooldown | 300 |
| requires_tools | ["bash"] |
| output | {"format":"markdown","artifacts":true,"artifact_type":"document"} |
Multi-source search, evidence compilation, and structured report generation for any research topic.
| Intent | Command | Key Params |
|---|---|---|
| Basic research | $PYTHON $SKILL_DIR/run.py --topic '...' | --topic (required) |
| Custom queries | $PYTHON $SKILL_DIR/run.py --topic '...' --queries '[...]' | --queries |
| Advanced depth | $PYTHON $SKILL_DIR/run.py --topic '...' --depth advanced | --depth |
$PYTHON $SKILL_DIR/run.py --topic 'Research topic' --queries '["keyword1","keyword2"]' --max_results 5 --depth basic
| Param | Type | Required | Description |
|---|---|---|---|
| topic | string | yes | Research topic |
| queries | string[] | no | Search keywords; defaults to 3 auto-generated queries |
| max_results | int | no | Results per query, default 5 |
| depth | string | no | basic or advanced |
| fetch_urls | string[] | no | Additional URLs to fetch full text from |
Returns JSON containing searches (search results), fetched_pages (fetched pages), and summary_prompt (synthesis prompt).
The LLM organizes results into a structured report: Problem, Findings/Evidence, Confidence Level, Impact/Recommendations.