/claude-research-skill
Decompose a research question into parallel agent workstreams, launch them, monitor progress, and synthesize results.
Claude Code
$ npx -y skills add altmbr/claude-research-skill --skill claude-research-skill --agent claude-code
Codex
$ npx skills add altmbr/claude-research-skill --skill claude-research-skill -a codex -y
Cursor
$ npx skills add altmbr/claude-research-skill --skill claude-research-skill -a cursor -y
Gemini CLI
$ npx skills add altmbr/claude-research-skill --skill claude-research-skill -a gemini-cli -y
GitHub Copilot
$ npx skills add altmbr/claude-research-skill --skill claude-research-skill -a github-copilot -y
OpenCode
$ npx skills add altmbr/claude-research-skill --skill claude-research-skill -a opencode -y
Windsurf
$ npx skills add altmbr/claude-research-skill --skill claude-research-skill -a windsurf -y
SKILL.md
claude-research-skill.SKILL.md/research — Multi-Agent Research Orchestrator
Decompose a research question into parallel agent workstreams, launch them, monitor progress, and synthesize results.
---
Phase 0.5: Social Signal Scan (Real-Time Pulse)
Before planning agents, run a quick social signal scan to see what people are **actually saying right now** about the topic. This informs agent scoping and prevents re-researching ground already covered.
**Run the last30days script (FOREGROUND, 5-minute timeout):**
# Find last30days skill root
for dir in \
"${CLAUDE_PLUGIN_ROOT:-}" \
"$HOME/.claude/skills/last30days" \
"$HOME/.agents/skills/last30days" \
"$HOME/.codex/skills/last30days"; do
[ -n "$dir" ] && [ -f "$dir/scripts/last30days.py" ] && SKILL_ROOT="$dir" && break
done
if [ -n "${SKILL_ROOT:-}" ]; then
export PATH="$HOME/Library/Python/3.9/bin:$PATH"
python3 "${SKILL_ROOT}/scripts/last30days.py" "{RESEARCH_TOPIC}" --emit=compact --agent
fi**If the script is available and returns results:**
1. Save the raw output to `research/[topic]/social_signal_scan.md` 2. Note the top signals: highest-engagement Reddit threads, most-liked X posts, relevant Polymarket odds 3. Use these to **inform agent scoping** in Phase 1:
- If Reddit/X surface a subtopic getting heavy discussion, ensure an agent covers it
- If Polymarket has relevant odds, feed them into risk/scenario agents
- If YouTube has relevant conference talks or demos, note URLs for agents
4. Provide the file path to agents as pre-loaded context:
"Pre-gathered social signal data is available at: [absolute path to social_signal_scan.md]
Read this file FIRST before searching. It contains recent Reddit threads, X posts,
YouTube videos, and Polymarket data with engagement metrics. Build on this — don't re-research it."
**If the script is NOT available** (missing skill or no API keys), skip this phase silently and proceed to Phase 1. Social data is supplementary, not required.
**When to skip this phase:**
- Historical research (events >30 days old)
- Highly technical/academic topics where social signal adds little value
- User explicitly says to skip it
---
Phase 1: Plan the Research
When the user asks to research something:
1. **Understand the question.** What exactly are we trying to learn? Who is it for? What decisions will it inform?
2. **Decompose into agent workstreams.** Each agent should have:
- A clear, non-overlapping scope (e.g., "Market sizing & competitive landscape", "Technical feasibility & architecture", "Regulatory & compliance landscape")
- 3-6 specific sections they must write
- A target output length (~500-1500 lines of markdown per agent is the sweet spot)
3. **Plan the synthesis agent.** This runs AFTER all research agents complete. Its job is to read all agent outputs and produce a single coherent synthesis document with cross-cutting insights, contradictions, and recommendations.
4. **Present the plan to the user.** Format:
## Research Plan: [Topic]
### Agent 1: [Name]
**Scope:** [1-2 sentence scope]
**Sections:**
1. [Section name]
2. [Section name]
3. ...
**Output file:** research/[topic]/[agent-name].md
### Agent 2: [Name]
...
### Synthesis Agent
**Runs after:** All research agents complete
**Output file:** research/[topic]/synthesis.md
5. **Wait for user approval** before proceeding. Do NOT launch agents until the user confirms the plan.
---
Phase 2: Create Skeleton Files
Once the user approves the plan:
1. **Create the output directory:** `research/[topic]/`
2. **For each research agent, create a skeleton markdown file** at the planned path. The skeleton MUST include:
# [Agent Name]: [Scope Title]
**Status:** IN PROGRESS
**Last updated:** [timestamp]
---
## CRITICAL INSTRUCTIONS FOR AGENT
> ⚠️ **YOU WILL BE STOPPED AND RELAUNCHED IF YOU VIOLATE THIS PROTOCOL.** ⚠️
>
> The ONLY acceptable pattern is: **Search → Edit → Search → Edit → Search → Edit.**
> NEVER: Search → Search. NO EXCEPTIONS. NOT EVEN ONCE.
>
> After EVERY search or fetch, IMMEDIATELY Edit this file with what you learned.
> If you do two searches in a row without an Edit to this file, you are VIOLATING THE PROTOCOL and will be killed.
>
> Work through sections in order. For each section:
> 1. Search/fetch for information
> 2. IMMEDIATELY write findings to this file under that section
> 3. Search/fetch for more information on the same section
> 4. IMMEDIATELY update this file with additional findings
> 5. Move to next section only after writing current section
>
> If a web fetch returns a 403 error, WRITE WHAT YOU HAVE before trying another URL.
>
> Every number needs a source. Every source needs a clickable URL inline.
> Do NOT collect sources at the end — put them inline with the facts.
>
> When you are DONE with all sections, change "Status: IN PROGRESS" to "Status: COMPLETE" at the top.
---
## 1. [First Section Name]
[To be filled by research agent]
## 2. [Second Section Name]
[To be filled by research agent]
...
3. **Also create the synthesis skeleton** with similar critical instructions, but noting it should read from the other agent output files.
---
Phase 3: Launch Research Agents
Launch ALL research agents in parallel using the Task tool with `run_in_background: true`.
Each agent prompt MUST include:
1. **The research question and their specific scope** — be precise about boundaries 2. **The exact file path they must write to** — absolute path 3. **The section list they must complete** — numbered, in order 4. **The critical write protocol** — copy verbatim:
CRITICAL WRITE PROTOCOL — READ THIS BEFORE DOING ANYTHING:
⚠️ YOU WILL BE STOPPED AND RELAUNCHED IF YOU VIOLATE THIS PROTOCOL. ⚠️
The ONLY acceptable pattern is: Search → Edit → Search → Edit → Search → Edit.
NEVER: Search → Search. NO EXCEPTIONS. NOT EVEN ONCE.
You MUST Edit your output file after EVERY SINGLE search or web fetch.
If you do two searches in a row witho
Read more
/research — Multi-Agent Research Orchestrator
Decompose a research question into parallel agent workstreams, launch them, monitor progress, and synthesize results.
---
Phase 0.5: Social Signal Scan (Real-Time Pulse)
Before planning agents, run a quick social signal scan to see what people are **actually saying right now** about the topic. This informs agent scoping and prevents re-researching ground already covered.
**Run the last30days script (FOREGROUND, 5-minute timeout):**
# Find last30days skill root
for dir in \
"${CLAUDE_PLUGIN_ROOT:-}" \
"$HOME/.claude/skills/last30days" \
"$HOME/.agents/skills/last30days" \
"$HOME/.codex/skills/last30days"; do
[ -n "$dir" ] && [ -f "$dir/scripts/last30days.py" ] && SKILL_ROOT="$dir" && break
done
if [ -n "${SKILL_ROOT:-}" ]; then
export PATH="$HOME/Library/Python/3.9/bin:$PATH"
python3 "${SKILL_ROOT}/scripts/last30days.py" "{RESEARCH_TOPIC}" --emit=compact --agent
fi**If the script is available and returns results:**
1. Save the raw output to `research/[topic]/social_signal_scan.md` 2. Note the top signals: highest-engagement Reddit threads, most-liked X posts, relevant Polymarket odds 3. Use these to **inform agent scoping** in Phase 1:
- If Reddit/X surface a subtopic getting heavy discussion, ensure an agent covers it
- If Polymarket has relevant odds, feed them into risk/scenario agents
- If YouTube has relevant conference talks or demos, note URLs for agents
4. Provide the file path to agents as pre-loaded context:
"Pre-gathered social signal data is available at: [absolute path to social_signal_scan.md] Read this file FIRST before searching. It contains recent Reddit threads, X posts, YouTube videos, and Polymarket data with engagement metrics. Build on this — don't re-research it."
**If the script is NOT available** (missing skill or no API keys), skip this phase silently and proceed to Phase 1. Social data is supplementary, not required.
**When to skip this phase:**
- Historical research (events >30 days old)
- Highly technical/academic topics where social signal adds little value
- User explicitly says to skip it
---
Phase 1: Plan the Research
When the user asks to research something:
1. **Understand the question.** What exactly are we trying to learn? Who is it for? What decisions will it inform?
2. **Decompose into agent workstreams.** Each agent should have:
- A clear, non-overlapping scope (e.g., "Market sizing & competitive landscape", "Technical feasibility & architecture", "Regulatory & compliance landscape")
- 3-6 specific sections they must write
- A target output length (~500-1500 lines of markdown per agent is the sweet spot)
3. **Plan the synthesis agent.** This runs AFTER all research agents complete. Its job is to read all agent outputs and produce a single coherent synthesis document with cross-cutting insights, contradictions, and recommendations.
4. **Present the plan to the user.** Format:
## Research Plan: [Topic] ### Agent 1: [Name] **Scope:** [1-2 sentence scope] **Sections:** 1. [Section name] 2. [Section name] 3. ... **Output file:** research/[topic]/[agent-name].md ### Agent 2: [Name] ... ### Synthesis Agent **Runs after:** All research agents complete **Output file:** research/[topic]/synthesis.md
5. **Wait for user approval** before proceeding. Do NOT launch agents until the user confirms the plan.
---
Phase 2: Create Skeleton Files
Once the user approves the plan:
1. **Create the output directory:** `research/[topic]/`
2. **For each research agent, create a skeleton markdown file** at the planned path. The skeleton MUST include:
# [Agent Name]: [Scope Title] **Status:** IN PROGRESS **Last updated:** [timestamp] --- ## CRITICAL INSTRUCTIONS FOR AGENT > ⚠️ **YOU WILL BE STOPPED AND RELAUNCHED IF YOU VIOLATE THIS PROTOCOL.** ⚠️ > > The ONLY acceptable pattern is: **Search → Edit → Search → Edit → Search → Edit.** > NEVER: Search → Search. NO EXCEPTIONS. NOT EVEN ONCE. > > After EVERY search or fetch, IMMEDIATELY Edit this file with what you learned. > If you do two searches in a row without an Edit to this file, you are VIOLATING THE PROTOCOL and will be killed. > > Work through sections in order. For each section: > 1. Search/fetch for information > 2. IMMEDIATELY write findings to this file under that section > 3. Search/fetch for more information on the same section > 4. IMMEDIATELY update this file with additional findings > 5. Move to next section only after writing current section > > If a web fetch returns a 403 error, WRITE WHAT YOU HAVE before trying another URL. > > Every number needs a source. Every source needs a clickable URL inline. > Do NOT collect sources at the end — put them inline with the facts. > > When you are DONE with all sections, change "Status: IN PROGRESS" to "Status: COMPLETE" at the top. --- ## 1. [First Section Name] [To be filled by research agent] ## 2. [Second Section Name] [To be filled by research agent] ...
3. **Also create the synthesis skeleton** with similar critical instructions, but noting it should read from the other agent output files.
---
Phase 3: Launch Research Agents
Launch ALL research agents in parallel using the Task tool with `run_in_background: true`.
Each agent prompt MUST include:
1. **The research question and their specific scope** — be precise about boundaries 2. **The exact file path they must write to** — absolute path 3. **The section list they must complete** — numbered, in order 4. **The critical write protocol** — copy verbatim:
CRITICAL WRITE PROTOCOL — READ THIS BEFORE DOING ANYTHING: ⚠️ YOU WILL BE STOPPED AND RELAUNCHED IF YOU VIOLATE THIS PROTOCOL. ⚠️ The ONLY acceptable pattern is: Search → Edit → Search → Edit → Search → Edit. NEVER: Search → Search. NO EXCEPTIONS. NOT EVEN ONCE. You MUST Edit your output file after EVERY SINGLE search or web fetch. If you do two searches in a row witho
A Claude Code skill that decomposes any research question into parallel agent workstreams, launches them simultaneously, monitors progress, and synthesizes results into a single coherent document. One command. Multiple agents.
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Questions about claude-research-skill.
- Which coding agents can use claude-research-skill?
- claude-research-skill installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

