AgentSkillsCN

agentic-research

共享团队深度代理研究作战手册。在代理研究系统中,所有代理(编排者、ExaAI专家、Firecrawl专家、NotebookLM专家)均遵循统一的沟通协议、来源质量分级、并行安全规则、输出格式标准,以及错误处理规范。

SKILL.md
--- frontmatter
name: agentic-research
version: 1.0.0
description: Shared team playbook for multi-agent deep research operations. Defines communication protocols, source quality tiers, parallel safety rules, output formatting standards, and error handling conventions used by all agents (orchestrator, ExaAI specialist, Firecrawl specialist, NotebookLM specialist) in the agentic research system.
metadata:
  clawdbot:
    emoji: "📋"
    requires:
      skills: ["exa", "firecrawl", "notebooklm", "agentic-research-orchestration"]

Agentic Research — Shared Team Playbook

This is the shared playbook loaded by ALL agents in the agentic research system. It defines the protocols, quality standards, and conventions that ensure consistent, high-quality research across the orchestrator and all specialist agents.

Every agent MUST read and follow this playbook before beginning work.

Team Structure

AgentRoleKey Tools
OrchestratorCoordinates workflow, relays URLs, synthesizes reportTeamCreate, SendMessage, Task
ExaAI SpecialistSemantic web search, source discoverymcp__exa__web_search_exa
Firecrawl SpecialistWeb scraping, site crawling, vector DBfirecrawl CLI, Qdrant
NotebookLM SpecialistAI-powered analysis, artifact generationnotebooklm CLI

Communication Protocol

Message Format

All inter-agent messages MUST use this structure:

code
## [Agent Name] [Message Type] (Batch N)

### [Section 1 Header]
- Item 1
- Item 2

### [Section 2 Header]
- Item 1

### Summary
Brief summary of key points.

Message Types

TypeWhenFromTo
URL ReportEvery 3-5 operationsSpecialistsOrchestrator
Progress UpdateEvery 5-10 operationsSpecialistsOrchestrator
Crawl RequestWhen docs site discoveredOrchestratorFirecrawl
Source RelayWhen high-quality URLs receivedOrchestratorNotebookLM
Completion SignalWhen all work doneSpecialistsOrchestrator
Error EscalationWhen blockedAny agentOrchestrator

URL Report Format (Specialists -> Orchestrator)

code
## [Agent] URL Report (Batch N)

### Key URLs Discovered:
- https://url1.com - [Description] - Tier: [Primary/Academic/Official/Industry/Community]
- https://url2.com - [Description] - Tier: [tier]

### Documentation Sites (recommend for Firecrawl):
- https://docs.example.com - Full documentation for X

### Key Findings:
- Finding 1
- Finding 2

Source Relay Format (Orchestrator -> NotebookLM)

code
Add these N sources to the notebook:
- https://url1.com — [Description] — Tier: Primary
- https://url2.com — [Description] — Tier: Academic

Completion Signal Format

code
[Agent] specialist complete. Findings written to findings/[agent]-findings.md.
[Key stats: searches, URLs, pages, etc.]
Key gaps: [list gaps].

Source Quality Tiers

All agents MUST classify discovered sources using these tiers. The orchestrator uses tiers to prioritize which URLs to relay to NotebookLM.

TierDescriptionPriorityExamples
PrimaryOriginal research, official announcements, creator contentHighestBlog posts by framework creators, official release notes, original research papers
AcademicPeer-reviewed papers, university research, conference proceedingsHigharXiv papers, ACM/IEEE publications, NeurIPS/ICML proceedings
OfficialOfficial documentation, guides, tutorials from project maintainersHighdocs.langchain.com, readthedocs sites, official GitHub READMEs
IndustryAnalysis from recognized industry analysts, reputable tech publicationsMediumHacker News (top posts), reputable tech blogs, benchmark reports
CommunityForum discussions, personal blogs, Stack Overflow, RedditLowerReddit threads, personal dev blogs, community wikis
NewsNews articles, press releases, general media coverageLowestTechCrunch, The Verge, general news sites

Tier Prioritization Rules

  1. Primary + Academic: Always relay to NotebookLM
  2. Official: Always relay to NotebookLM (essential for technical accuracy)
  3. Industry: Relay if relevant to key questions and not redundant
  4. Community: Only relay if contains unique insights not found in higher tiers
  5. News: Rarely relay -- only if contains exclusive information

Source Limit Management

  • NotebookLM limit: 300 sources (paid plan), 50 (standard)
  • Target: 200 excellent sources > 300 mediocre ones
  • Track count: Orchestrator maintains running total
  • Stop early: If quality sources are exhausted before hitting limit

See references/source-quality-tiers.md for detailed tier classification examples.

Parallel Safety Rules

NotebookLM Commands

CRITICAL: ALL agents MUST follow these rules.

  • ALWAYS use -n <notebook_id> or --notebook <notebook_id> flags
  • NEVER use notebooklm use <id> -- it modifies shared state and is unsafe in parallel workflows
  • Use full UUIDs in automation to avoid ambiguity from partial IDs
  • Use --new flag on ask commands when switching topic areas (avoids conversation ID conflicts)

File System Safety

  • Each specialist writes to its own findings file (no conflicts):
    • ExaAI: findings/exa-findings.md
    • Firecrawl: findings/firecrawl-findings.md
    • NotebookLM: findings/notebooklm-findings.md
  • Only the orchestrator writes to report.md and sources/sources.md
  • Artifacts are downloaded to artifacts/ (NotebookLM specialist only)

Team Communication Safety

  • All messages go through SendMessage tool (not shared files)
  • Messages are automatically delivered -- no polling needed
  • Each agent maintains its own state independently
  • The orchestrator is the only agent that reads all findings files (during synthesis)

Output Formatting Standards

Findings Files

All specialist findings files MUST include:

  1. Research Topic -- exact topic from brief
  2. Methodology Summary -- what was done, key stats
  3. Key Findings -- organized by topic area, with inline source URLs
  4. Contradictions -- where sources disagree (do NOT smooth over)
  5. Gaps -- what couldn't be found or needs more investigation

Source Citation Format

Inline citations use markdown links:

markdown
According to the official documentation [Source Title](https://url), the framework supports...

When citing multiple sources:

markdown
Multiple sources confirm this approach [Source A](url1), [Source B](url2), though [Source C](url3) disagrees.

URL Reporting Format

When reporting URLs, always include:

  • Full URL (no shortlinks)
  • Brief description (what the page contains)
  • Quality tier classification
code
- https://docs.example.com/guide - Comprehensive setup guide - Tier: Official

Error Handling Protocol

Severity Levels

LevelActionExamples
WarningLog and continueRate limit on one site, single source fails to load
ErrorReport to orchestrator, attempt workaroundAuth failure, major site blocked, tool crash
CriticalReport to orchestrator immediately, stop workAll tools failing, auth completely broken

Error Reporting Format

code
## Error Report

**Agent:** [name]
**Severity:** [Warning/Error/Critical]
**Error:** [description]
**Action Taken:** [what you tried]
**Impact:** [what's affected]
**Suggested Fix:** [if known]

Recovery Strategies

  1. Rate limits: Exponential backoff (30s -> 2min -> skip)
  2. Auth failures: Run diagnostic commands, report to orchestrator
  3. Tool crashes: Retry once, then report
  4. Network issues: Wait 1 minute, retry, then report
  5. Source not found: Log, skip, continue with other sources

Persistent Memory Conventions

All agents write session learnings to ~/.claude/memory/:

AgentMemory File
Orchestrator~/.claude/memory/agentic-orchestrator.md
ExaAI~/.claude/memory/exa-specialist.md
Firecrawl~/.claude/memory/firecrawl-specialist.md
NotebookLM~/.claude/memory/notebooklm-specialist.md

Memory Entry Format

markdown
## Session: YYYY-MM-DD -- <topic-slug>

**What worked:**
- [insight 1]
- [insight 2]

**What didn't work:**
- [issue 1]

**Lessons learned:**
- [lesson 1]

Memory Usage

  • Read memory at session start to leverage past learnings
  • Write memory at session end with insights from current session
  • Keep entries concise -- focus on actionable insights
  • Update or remove entries that turn out to be wrong

Cross-References

This playbook is used by:

  • Orchestrator agent: agents/agentic-orchestrator.md
  • ExaAI specialist agent: agents/exa-specialist.md
  • Firecrawl specialist agent: agents/firecrawl-specialist.md
  • NotebookLM specialist agent: agents/notebooklm-specialist.md

Related skills:

  • Orchestration methodology: skills/agentic-research-orchestration/SKILL.md
  • ExaAI search: skills/exa/SKILL.md
  • Firecrawl web scraping: skills/firecrawl/SKILL.md
  • NotebookLM automation: skills/notebooklm/SKILL.md