AgentSkillsCN

foundry-research

具备五种工作流的 AI 驱动研究技能——聊天模式(单模型对话)、共识模式(多模型融合)、深思模式(系统性探究)、创意思考模式(创意头脑风暴),以及深度模式(多阶段网络调研)。支持持久线程与研究会话。

SKILL.md
--- frontmatter
name: foundry-research
description: AI-powered research skill with five workflows - chat (single-model conversation), consensus (multi-model synthesis), thinkdeep (systematic investigation), ideate (creative brainstorming), and deep (multi-phase web research). Supports persistent threads and research sessions.

Research Skill

Overview

  • Purpose: AI-powered research with multiple reasoning strategies
  • Scope: Five workflows, persistent thread and session management
  • Entry: Skill(foundry:foundry-research) or user invocation

Flow

[x?]=decision (GATE)=user approval =sequence

code
- **Entry** → [route?]
  - [explicit?] → Dispatch → Execute → Persist thread → Response + thread_id
  - [thread-id?] → Resume → Dispatch → Execute → Persist thread → Response + thread_id
  - [research-id?] → SessionMgmt
  - [sessions?] → ListSessions
  - [no args?] → (GATE: choose workflow) → AutoRoute → Dispatch → Execute → Persist thread → Response + thread_id
  - [deep?] → Start → Poll → Report (background execution)

CRITICAL for deep workflow: Read references/deep-research-workflow.md before execution. Contains required polling strategy and MCP parameters.

Deep Research Polling Protocol (MANDATORY)

BEFORE EVERY status check, you MUST:

  1. Generate user-facing text about current progress
  2. Do NOT call deep-research-status immediately after another MCP tool
  3. Track your check count (max 5)
Check #What to Say
1"Research underway. Currently in {phase} phase..."
2-3"Progress: {queries_completed}/{total} queries done..."
4"Still working ({elapsed} minutes)..."
5Stop polling, use AskUserQuestion with options

Stall Detection: Only after elapsed_ms > 300000 AND no progress change.

NO INDEPENDENT RESEARCH: While deep research is running, do NOT use WebSearch, WebFetch, or other research tools. The deep research workflow handles all web gathering - doing your own searches is redundant and wastes resources.

MCP Tooling

RouterActions
researchchat, consensus, thinkdeep, ideate, deep-research, deep-research-status, deep-research-report, deep-research-list, deep-research-delete, thread-list, thread-get, thread-delete, node-execute, node-record, node-status, node-findings

MCP Contract

ActionRequiredOptionalErrors
chatpromptthread_id, provider_idTHREAD_NOT_FOUND
consensuspromptproviders, strategyNO_MODELS_AVAILABLE
thinkdeeppromptthread_id, depthMAX_DEPTH_EXCEEDED
ideatepromptthread_id, phaseINVALID_PHASE
deep-researchquerymax_iterations, max_sub_queries, follow_linksRESEARCH_TIMEOUT
deep-research-statusresearch_id-RESEARCH_NOT_FOUND
deep-research-reportresearch_id-RESEARCH_NOT_FOUND
deep-research-list-limit, completed_only-
deep-research-deleteresearch_id-RESEARCH_NOT_FOUND
thread-*thread_idlimitTHREAD_NOT_FOUND
node-statusspec_id, research_node_id-NODE_NOT_FOUND
node-executespec_id, research_node_idpromptNODE_NOT_FOUND, INVALID_TYPE
node-recordspec_id, research_node_id, resultsummary, key_insights, recommendations, confidenceNODE_NOT_FOUND
node-findingsspec_id, research_node_id-NODE_NOT_FOUND, NO_FINDINGS

Workflow Selection

SignalWorkflow
Follow-up, iterationchat
Multiple perspectivesconsensus
Complex problemthinkdeep
Brainstormingideate
Comprehensive research, multiple sourcesdeep

User Gates

  • No args: workflow selection
  • Ambiguous: clarify before auto-route
  • Consensus: strategy selection
  • Ideate: phase transition
  • Deep: progress updates during background execution

Output Formats

WorkflowResponse
chat{response, thread_id, model}
consensus{responses[], synthesis, strategy}
thinkdeep{findings[], confidence, thread_id}
ideate{ideas[], phase, selected[]}
deep{research_id, status, report{summary, findings[], sources[]}}

References