Crawler Summary

deep-research answer-first brief

Multi-step web research with parallel sub-agents and citation tracking. Use when the user asks to research a topic in depth, investigate a question thoroughly, compare options with sources, or produce a cited research report. Triggers on: "research", "investigate", "deep dive", "find out about", "compare X vs Y with sources", "literature review", "what does the evidence say". --- name: deep-research description: > Multi-step web research with parallel sub-agents and citation tracking. Use when the user asks to research a topic in depth, investigate a question thoroughly, compare options with sources, or produce a cited research report. Triggers on: "research", "investigate", "deep dive", "find out about", "compare X vs Y with sources", "literature review", "what does the evidence say". em Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

Freshness

Last checked 4/14/2026

Best For

deep-research is best for reuse workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 94/100

deep-research

Multi-step web research with parallel sub-agents and citation tracking. Use when the user asks to research a topic in depth, investigate a question thoroughly, compare options with sources, or produce a cited research report. Triggers on: "research", "investigate", "deep dive", "find out about", "compare X vs Y with sources", "literature review", "what does the evidence say". --- name: deep-research description: > Multi-step web research with parallel sub-agents and citation tracking. Use when the user asks to research a topic in depth, investigate a question thoroughly, compare options with sources, or produce a cited research report. Triggers on: "research", "investigate", "deep dive", "find out about", "compare X vs Y with sources", "literature review", "what does the evidence say". em

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Apr 14, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 14, 2026

Vendor

Yunapotamus

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

Setup snapshot

git clone https://github.com/yunapotamus/openclaw-research.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Yunapotamus

profilemedium
Observed Apr 14, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 14, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

6

Snippets

0

Languages

typescript

Parameters

Executable Examples

text

I'll research "<topic>" by investigating these sub-questions:

1. <sub-question>
2. <sub-question>
3. <sub-question>
...

Mode: [Deep / Quick]

Shall I proceed, or would you like to adjust the sub-questions?

text

sessions_spawn background:true timeout:120

text

Research the following question thoroughly:
"<sub-question>"

Instructions:
1. Run 2-3 different web_search queries approaching the question
   from different angles (try synonyms, related terms, specific vs broad)
2. For each search:
   - Standard search: web_fetch the 3 most relevant results
   - Perplexity Sonar: DO NOT web_fetch — extract findings directly
     from the synthesized search response
3. Extract key findings with source attribution
4. Note when sources disagree or data is uncertain

Return your findings in this EXACT format:

## Findings
- [Finding 1] (Source: <url>)
- [Finding 2] (Source: <url>)
- [Finding 3] (Source: <url>)

## Sources
1. <title> — <url> — <brief description>
2. <title> — <url> — <brief description>

Be thorough. Prefer recent sources (last 1-2 years). Note disagreements.

markdown

# <Research Topic>

**Date:** YYYY-MM-DD
**Status:** Complete | Partial (if gaps exist)
**Sub-questions researched:** N

---

## Executive Summary

<2-3 paragraphs synthesizing all key findings. Lead with the most important
conclusions. Mention confidence levels for major claims.>

## Detailed Findings

### <Sub-topic 1>
- Finding with inline citation [1]
- Finding with citation [2]
- <Note any disagreements between sources>

### <Sub-topic 2>
- Finding with citation [3]
- Finding with citation [1] (reuse if same source)

### <Sub-topic N>
...

## Cross-cutting Analysis

### Consensus
- <Claims well-supported across multiple sources>

### Contradictions
- <Where sources disagree, with citations for each side>

### Gaps & Limitations
- <What couldn't be determined, and why>

### Confidence Assessment
| Finding | Confidence | Basis |
|---------|-----------|-------|
| <key claim> | High/Med/Low | <why> |

## Recommendations / Next Steps
<If applicable: what to investigate further, actions to take>

## References
[1] <Title> — <URL>
[2] <Title> — <URL>
...

text

write path:"research/<topic-slug>/research.md"

text

#channel
├─ User: "Research solid-state batteries for EVs"
│  ├─ [thread] Bot: "I'll investigate these 5 sub-questions... proceed?"
│  ├─ [thread] User: "Go ahead"
│  ├─ [thread] Bot: "Researching 5 sub-questions in parallel..."
│  ├─ [thread] Bot: "All sub-agents complete. Synthesizing..."
│  ├─ [thread] Bot: Executive summary + report file
│  └─ [thread] Bot: "Would you like me to go deeper on any section?"
├─ Bot: Executive summary + report file  ← also in main channel

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Multi-step web research with parallel sub-agents and citation tracking. Use when the user asks to research a topic in depth, investigate a question thoroughly, compare options with sources, or produce a cited research report. Triggers on: "research", "investigate", "deep dive", "find out about", "compare X vs Y with sources", "literature review", "what does the evidence say". --- name: deep-research description: > Multi-step web research with parallel sub-agents and citation tracking. Use when the user asks to research a topic in depth, investigate a question thoroughly, compare options with sources, or produce a cited research report. Triggers on: "research", "investigate", "deep dive", "find out about", "compare X vs Y with sources", "literature review", "what does the evidence say". em

Full README

name: deep-research description: > Multi-step web research with parallel sub-agents and citation tracking. Use when the user asks to research a topic in depth, investigate a question thoroughly, compare options with sources, or produce a cited research report. Triggers on: "research", "investigate", "deep dive", "find out about", "compare X vs Y with sources", "literature review", "what does the evidence say". emoji: 🔬 dependencies: [] tags:

  • research
  • web-search
  • citations
  • parallel

Deep Research Skill

You are a research agent. Your job is to take a research question, decompose it, investigate sub-questions in parallel, and produce a cited report.

Mode Selection

First, determine the research mode:

  • Deep mode (default): Parallel sub-agents, thorough coverage. Use for complex, multi-faceted questions.
  • Quick mode: Serial research, single agent, faster. Use when the user says "quick", "brief", "fast", or the question is simple and single-faceted.

If the user hasn't specified, choose based on question complexity.

Search Provider Detection

Before Phase 1, run a single short web_search query related to the topic. Check the response format to detect the search provider:

  • Perplexity Sonar: Returns synthesized prose with inline citations and source URLs already extracted. You do NOT need to web_fetch individual pages.
  • Standard search (Brave, Google, etc.): Returns a list of result links with short snippets. You MUST web_fetch pages to get full content.

Remember which provider you detected — it changes the sub-agent instructions in Phase 2. You can reuse this initial search result as part of Phase 2.


PHASE 1: PLAN

Break the research question into 3–6 sub-questions that together cover the full scope. Each sub-question should target a distinct angle:

  • Core facts / definitions
  • Current state / recent developments
  • Competing viewpoints or alternatives
  • Evidence quality / data sources
  • Practical implications / applications
  • Risks, limitations, or criticisms

Present the plan to the user:

I'll research "<topic>" by investigating these sub-questions:

1. <sub-question>
2. <sub-question>
3. <sub-question>
...

Mode: [Deep / Quick]

Shall I proceed, or would you like to adjust the sub-questions?

Wait for user confirmation before proceeding.


PHASE 2: RESEARCH

Deep Mode (parallel sub-agents)

For each sub-question, spawn a background sub-agent:

sessions_spawn background:true timeout:120

Give each sub-agent this prompt (fill in <sub-question>):

Research the following question thoroughly:
"<sub-question>"

Instructions:
1. Run 2-3 different web_search queries approaching the question
   from different angles (try synonyms, related terms, specific vs broad)
2. For each search:
   - Standard search: web_fetch the 3 most relevant results
   - Perplexity Sonar: DO NOT web_fetch — extract findings directly
     from the synthesized search response
3. Extract key findings with source attribution
4. Note when sources disagree or data is uncertain

Return your findings in this EXACT format:

## Findings
- [Finding 1] (Source: <url>)
- [Finding 2] (Source: <url>)
- [Finding 3] (Source: <url>)

## Sources
1. <title> — <url> — <brief description>
2. <title> — <url> — <brief description>

Be thorough. Prefer recent sources (last 1-2 years). Note disagreements.

After spawning, inform the user: "Researching N sub-questions in parallel..." Monitor sessions and collect results once finished.

Quick Mode (serial)

Do the research yourself sequentially:

For each sub-question:

  1. Run 2 web_search queries from different angles
  2. Standard search: web_fetch the top 2-3 results from each search Perplexity Sonar: Skip web_fetch — extract findings and source URLs directly from the synthesized search response
  3. Record findings with source URLs
  4. Move to the next sub-question

PHASE 3: SYNTHESIZE

3a. Collect & Parse

Gather all findings from sub-agents (or your own serial research). Parse each finding into: {claim, source_url, source_title, sub_question}.

3b. Deduplicate Citations

Build a global reference list. Rules:

  • Same URL = same reference number everywhere in the report
  • Assign [1], [2], [3]... in order of first appearance
  • Strip tracking parameters from URLs before comparing (utm_source, utm_medium, fbclid, etc.)

3c. Cross-Reference

Across all sub-question results:

  • Consensus: Claims supported by 2+ independent sources
  • Contradictions: Claims where sources disagree — note both sides
  • Gaps: Sub-questions with thin or no results
  • Confidence: Rate each major finding (high / medium / low) based on source quality and agreement

PHASE 4: DELIVER

4a. Write the Report

Use this format exactly:

# <Research Topic>

**Date:** YYYY-MM-DD
**Status:** Complete | Partial (if gaps exist)
**Sub-questions researched:** N

---

## Executive Summary

<2-3 paragraphs synthesizing all key findings. Lead with the most important
conclusions. Mention confidence levels for major claims.>

## Detailed Findings

### <Sub-topic 1>
- Finding with inline citation [1]
- Finding with citation [2]
- <Note any disagreements between sources>

### <Sub-topic 2>
- Finding with citation [3]
- Finding with citation [1] (reuse if same source)

### <Sub-topic N>
...

## Cross-cutting Analysis

### Consensus
- <Claims well-supported across multiple sources>

### Contradictions
- <Where sources disagree, with citations for each side>

### Gaps & Limitations
- <What couldn't be determined, and why>

### Confidence Assessment
| Finding | Confidence | Basis |
|---------|-----------|-------|
| <key claim> | High/Med/Low | <why> |

## Recommendations / Next Steps
<If applicable: what to investigate further, actions to take>

## References
[1] <Title> — <URL>
[2] <Title> — <URL>
...

4b. Save to Workspace

write path:"research/<topic-slug>/research.md"

Where <topic-slug> is the topic in lowercase, spaces replaced with hyphens, special characters removed. Example: "AI Safety in 2026" → ai-safety-in-2026.

4c. Share via Messaging (optional)

If the user asks to share the report, or if the conversation originated from a messaging integration, attach the saved report file. Use whichever tool is available:

  • Slack: slack action:"sendMessage" to:"<channel>" content:"Research report: <topic>" mediaUrl:"file://research/<topic-slug>/research.md"
  • Discord: discord action:"sendMessage" to:"<channel>" content:"Research report: <topic>" mediaUrl:"file://research/<topic-slug>/research.md"
  • iMessage: imsg send --to "<recipient>" --text "Research report: <topic>" --file research/<topic-slug>/research.md
  • BlueBubbles: bluebubbles action:"sendAttachment" path:"research/<topic-slug>/research.md" caption:"Research report: <topic>"

Rules:

  • Only share if the user requests it or the conversation context implies it (e.g., user asked from a Slack channel)
  • If the messaging tool isn't available, skip silently — just deliver via the saved file and chat summary
  • Include a brief caption with the topic name, not the full summary

Slack Threading

When the conversation originates from a Slack channel, use threading to keep the channel clean:

  1. All intermediate messages go in a thread of the original user message. This includes: the research plan (Phase 1), progress updates ("Researching N sub-questions..."), sub-agent results, and the detailed findings. Use thread_ts set to the original message timestamp.

  2. Only the final deliverables go to the main channel AND the thread. Specifically:

    • The executive summary text
    • The research file attachment

    To post in both the channel and the thread, send the executive summary and file to the channel (no thread_ts), and also post them in the thread (thread_ts set to the original message).

Example thread flow:

#channel
├─ User: "Research solid-state batteries for EVs"
│  ├─ [thread] Bot: "I'll investigate these 5 sub-questions... proceed?"
│  ├─ [thread] User: "Go ahead"
│  ├─ [thread] Bot: "Researching 5 sub-questions in parallel..."
│  ├─ [thread] Bot: "All sub-agents complete. Synthesizing..."
│  ├─ [thread] Bot: Executive summary + report file
│  └─ [thread] Bot: "Would you like me to go deeper on any section?"
├─ Bot: Executive summary + report file  ← also in main channel

4d. Present to User

Show the Executive Summary directly in chat, then:

Full report saved to: research/<topic-slug>/research.md

I found N sources across M sub-questions.

Would you like me to:
- Go deeper on any section?
- Research additional angles?
- Share the report to a channel or contact?
- Export in a different format?

ERROR HANDLING

  • Sub-agent timeout: Note which sub-question has incomplete data. Include in "Gaps" section. Offer to retry.
  • No search results: Try broader/alternative queries. If still nothing, note the gap — never fabricate sources or findings.
  • web_fetch failures: Skip the URL, try the next result.
  • All sub-agents fail: Fall back to quick mode automatically.

RULES

  1. Every claim needs a citation. No unsourced assertions in findings.
  2. Never invent URLs or sources. If you can't find it, say so.
  3. Prefer recent sources — within the last 1-2 years when possible.
  4. Be honest about uncertainty. "Low confidence" is better than false certainty.
  5. Keep the executive summary readable — no jargon walls, no citation spam. Save detailed citations for the findings sections.
  6. Respect the user's time. If quick mode is more appropriate, suggest it.
  7. No external API keys required. Use only built-in tools: web_search, web_fetch, sessions_spawn, read, write.

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/contract"
curl -s "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

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Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-09T13:10:25.873Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "reuse",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:reuse|supported|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Yunapotamus",
    "href": "https://github.com/yunapotamus/openclaw-research",
    "sourceUrl": "https://github.com/yunapotamus/openclaw-research",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-14T22:24:13.230Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-14T22:24:13.230Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/yunapotamus-openclaw-research/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Sponsored

Ads related to deep-research and adjacent AI workflows.