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
| Agent | Role | Key Tools |
|---|---|---|
| Orchestrator | Coordinates workflow, relays URLs, synthesizes report | TeamCreate, SendMessage, Task |
| ExaAI Specialist | Semantic web search, source discovery | mcp__exa__web_search_exa |
| Firecrawl Specialist | Web scraping, site crawling, vector DB | firecrawl CLI, Qdrant |
| NotebookLM Specialist | AI-powered analysis, artifact generation | notebooklm CLI |
Communication Protocol
Message Format
All inter-agent messages MUST use this structure:
## [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
| Type | When | From | To |
|---|---|---|---|
| URL Report | Every 3-5 operations | Specialists | Orchestrator |
| Progress Update | Every 5-10 operations | Specialists | Orchestrator |
| Crawl Request | When docs site discovered | Orchestrator | Firecrawl |
| Source Relay | When high-quality URLs received | Orchestrator | NotebookLM |
| Completion Signal | When all work done | Specialists | Orchestrator |
| Error Escalation | When blocked | Any agent | Orchestrator |
URL Report Format (Specialists -> Orchestrator)
## [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)
Add these N sources to the notebook: - https://url1.com — [Description] — Tier: Primary - https://url2.com — [Description] — Tier: Academic
Completion Signal Format
[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.
| Tier | Description | Priority | Examples |
|---|---|---|---|
| Primary | Original research, official announcements, creator content | Highest | Blog posts by framework creators, official release notes, original research papers |
| Academic | Peer-reviewed papers, university research, conference proceedings | High | arXiv papers, ACM/IEEE publications, NeurIPS/ICML proceedings |
| Official | Official documentation, guides, tutorials from project maintainers | High | docs.langchain.com, readthedocs sites, official GitHub READMEs |
| Industry | Analysis from recognized industry analysts, reputable tech publications | Medium | Hacker News (top posts), reputable tech blogs, benchmark reports |
| Community | Forum discussions, personal blogs, Stack Overflow, Reddit | Lower | Reddit threads, personal dev blogs, community wikis |
| News | News articles, press releases, general media coverage | Lowest | TechCrunch, The Verge, general news sites |
Tier Prioritization Rules
- •Primary + Academic: Always relay to NotebookLM
- •Official: Always relay to NotebookLM (essential for technical accuracy)
- •Industry: Relay if relevant to key questions and not redundant
- •Community: Only relay if contains unique insights not found in higher tiers
- •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
--newflag onaskcommands 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
- •ExaAI:
- •Only the orchestrator writes to
report.mdandsources/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:
- •Research Topic -- exact topic from brief
- •Methodology Summary -- what was done, key stats
- •Key Findings -- organized by topic area, with inline source URLs
- •Contradictions -- where sources disagree (do NOT smooth over)
- •Gaps -- what couldn't be found or needs more investigation
Source Citation Format
Inline citations use markdown links:
According to the official documentation [Source Title](https://url), the framework supports...
When citing multiple sources:
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
- https://docs.example.com/guide - Comprehensive setup guide - Tier: Official
Error Handling Protocol
Severity Levels
| Level | Action | Examples |
|---|---|---|
| Warning | Log and continue | Rate limit on one site, single source fails to load |
| Error | Report to orchestrator, attempt workaround | Auth failure, major site blocked, tool crash |
| Critical | Report to orchestrator immediately, stop work | All tools failing, auth completely broken |
Error Reporting Format
## 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
- •Rate limits: Exponential backoff (30s -> 2min -> skip)
- •Auth failures: Run diagnostic commands, report to orchestrator
- •Tool crashes: Retry once, then report
- •Network issues: Wait 1 minute, retry, then report
- •Source not found: Log, skip, continue with other sources
Persistent Memory Conventions
All agents write session learnings to ~/.claude/memory/:
| Agent | Memory 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
## 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