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Deep Research

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seaworld008
deep-research

Produce source-backed research reports, literature reviews, or technical and market briefs when evidence tracking and a defined report format matter.

Overview

Publisherseaworld008
RepositoryCommonly-used-high-value-skills
Skill namedeep-research
Stars
70
Forks
11
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by seaworld008 on GitHub. Read the source before you install it.

Installation

Install the Deep Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-skills.git /tmp/Commonly-used-high-value-skills
mkdir -p .claude/skills
cp -r /tmp/Commonly-used-high-value-skills/openclaw-skills/deep-research .claude/skills/deep-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deep Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Deep Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Deep Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Deep Research

Create high-fidelity research reports with strict format control, evidence mapping, and multi-pass synthesis.

Quick Start

  1. Clarify the report spec and format contract
  2. Build a research plan and query set
  3. Collect evidence with the deepresearch tool (multi-pass if needed)
  4. Triage sources and build an evidence table
  5. Draft the full report in multiple complete passes (parallel subagents)
  6. UNION merge, enforce format compliance, verify citations
  7. Present draft for human review and iterate

Core Workflow

Copy this checklist and track progress:

Deep Research Progress:
- [ ] Step 1: Intake and format contract
- [ ] Step 2: Research plan and query set
- [ ] Step 3: Evidence collection (deepresearch tool)
- [ ] Step 4: Source triage and evidence table
- [ ] Step 5: Outline and section map
- [ ] Step 6: Multi-pass full drafting (parallel subagents)
- [ ] Step 7: UNION merge and format compliance
- [ ] Step 8: Evidence and citation verification
- [ ] Step 9: Present draft for human review and iterate

Step 1: Intake and Format Contract

Establish the report requirements before any research:

  • Confirm audience, purpose, scope, time range, and geography
  • Lock output format: Markdown, DOCX, slides, or user-provided template
  • Capture required sections and exact formatting rules
  • Confirm citation style (footnotes, inline, numbered, APA, etc.)
  • Confirm length targets per section
  • Ask for any existing style guide or sample report

Create a concise report spec file:

Report Spec:
- Audience:
- Purpose:
- Scope:
- Time Range:
- Geography:
- Required Sections:
- Section Formatting Rules:
- Citation Style:
- Output Format:
- Length Targets:
- Tone:
- Must-Include Sources:
- Must-Exclude Topics:

If a user provides a template or an example report, treat it as a hard constraint and mirror the structure.

Step 2: Research Plan and Query Set

Define the research strategy before calling tools:

  • Break the main question into 3-7 subquestions
  • Define key entities, keywords, and synonyms
  • Identify primary sources vs secondary sources
  • Define disqualifiers (outdated, low quality, opinion-only)
  • Assemble a query set per section

Use references/research_plan_checklist.md for guidance.

Step 3: Evidence Collection (Deepresearch Tool)

Use the deepresearch tool to collect evidence and citations.

  • Run multiple complete passes if coverage is uncertain
  • Vary query phrasing to reduce blind spots
  • Preserve raw tool output in files for traceability

File structure (recommended):

<output_dir>/research/<topic-name>/
  deepresearch_pass1.md
  deepresearch_pass2.md
  deepresearch_pass3.md

If deepresearch is unavailable, rely on user-provided sources only and state limitations explicitly.

Step 4: Source Triage and Evidence Table

Normalize and score sources before drafting:

Evidence table minimum columns:

  • Source ID
  • Title
  • Publisher
  • Date
  • URL or reference
  • Quality tier (A/B/C)
  • Notes

Step 5: Outline and Section Map

Create an outline that enforces the format contract:

Step 6: Multi-Pass Full Drafting (Parallel Subagents)

Avoid single-pass drafting; generate multiple complete reports, then merge.

Preferred Strategy: Parallel Subagents (Complete Draft Each)

Use the Task tool to spawn parallel subagents with isolated context. Each subagent must:

  • Load the report spec, outline, and evidence table
  • Draft the FULL report (all sections)
  • Enforce formatting rules and citation style

Implementation pattern:

Task(subagent_type="general-purpose", prompt="Draft complete report ...", run_in_background=false) -> version1.md
Task(subagent_type="general-purpose", prompt="Draft complete report ...", run_in_background=false) -> version2.md
Task(subagent_type="general-purpose", prompt="Draft complete report ...", run_in_background=false) -> version3.md

Write drafts to files, not conversation context:

<output_dir>/intermediate/<topic-name>/version1.md
<output_dir>/intermediate/<topic-name>/version2.md
<output_dir>/intermediate/<topic-name>/version3.md

Step 7: UNION Merge and Format Compliance

Merge using UNION, never remove content without evidence-based justification:

  • Keep all unique findings from all versions
  • Consolidate duplicates while preserving the most detailed phrasing
  • Ensure every claim in the merged draft has a cited source
  • Enforce the exact section order, headings, and formatting
  • Re-run formatting rules from references/formatting_rules.md

Step 8: Evidence and Citation Verification

Verify traceability:

  • Every numeric claim has at least one source
  • Every recommendation references supporting evidence
  • No orphan claims without citations
  • Dates and time ranges are consistent
  • Conflicts are explicitly called out with both sources

Use references/completeness_review_checklist.md.

Step 9: Present Draft for Human Review and Iterate

Present the draft as a reviewable version:

  • Emphasize that format compliance and factual accuracy need human review
  • Accept edits to format, structure, and scope
  • If the user provides another AI output, cross-compare and UNION merge

Output Requirements

  • Match the requested language and tone
  • Preserve technical terms in English
  • Respect the report spec and formatting rules
  • Include a references section or bibliography

Reference Files

FileWhen to Load
research_report_template.mdBuild outline and draft structure
formatting_rules.mdEnforce section formatting and citation rules
source_quality_rubric.mdScore and triage sources
research_plan_checklist.mdBuild research plan and query set
completeness_review_checklist.mdReview for coverage, citations, and compliance

Anti-Patterns

  • Single-pass drafting without parallel complete passes
  • Splitting passes by section instead of full report drafts
  • Ignoring the format contract or user template
  • Claims without citations or evidence table mapping
  • Mixing conflicting dates without calling out discrepancies
  • Copying external AI output without verification
  • Deleting intermediate drafts or raw research outputs

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Deep Research AI skill do?

Produce source-backed research reports, literature reviews, or technical and market briefs when evidence tracking and a defined report format matter.

Why use Deep Research on TypingMind?

Because you install it once and use it with any model. Deep Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Deep Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/seaworld008/Commonly-used-high-value-skills/tree/main/openclaw-skills/deep-research. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Deep Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Deep Research?

As many as you like. As long as a model supports skills, you can use Deep Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Deep Research AI skill free?

Yes. It is published on GitHub by seaworld008 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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