manus — Claude Code skill: hand long tasks to the Manus agent
This skill forwards slow research jobs to the Manus agent, which browses the web and returns a report with attached files.
npx skills add sanjay3290/ai-skills --skill manus -a claude-codeWhat manus does
The skill wraps the Manus API. Your agent creates a task, gets a task_id back, then polls until the status reads completed or failed. Output text and file attachments come out of the same response — markdown reports, CSVs, charts.
Everything runs through curl against https://api.manus.ai: task creation, status checks, task listing, follow-up turns via taskId, deletion, and projects that carry shared instructions. Pick the agent profile by workload — manus-1.6-lite for quick lookups, manus-1.6-max for multi-source analysis.
You need MANUS_API_KEY in your environment. Without it every call fails on auth, so set the key before the first run. Polling advice in the skill: every 5–10 seconds for simple jobs, 15–30 seconds for research.
What it helps with
- compare 4K monitors in a spec-and-price table
- pull a ticker profile with a one-year price chart
- merge several sources into one market overview
- get CSVs and charts alongside written output
- start a long job and return to it later by
task_id
Example prompts for the agent
- Delegate to Manus: find 4K monitors for Mac with Thunderbolt and 120Hz+, last year's models only, output a table
- Send Manus a stock analysis for AAPL with a one-year price chart
- Check the Manus session status and show me the task link
How to install manus
1Skills CLI (Vercel)
npx skills add sanjay3290/ai-skills --skill manus -a claude-code2Manually: put the files in place
~/.claude/skills/manus/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/manus/
1Skills CLI (Vercel)
npx skills add sanjay3290/ai-skills --skill manus -a codex2Manually: put the files in place
.agents/skills/manus/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add sanjay3290/ai-skills --skill manus -a cursor2Manually: put the files in place
.cursor/skills/manus/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install sanjay3290/ai-skills manus2Manually: put the files in place
.github/skills/manus/SKILL.md1Skills CLI (Vercel)
npx skills add sanjay3290/ai-skills --skill manus -a gemini-cli2Platform CLI
gemini skills install https://github.com/sanjay3290/ai-skills --path skills/manusManually: put the files in place
.devin/skills/manus/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add sanjay3290/ai-skills --skill manus -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about manus
How do I install manus in Claude Code?
Run npx skills add sanjay3290/ai-skills --skill manus -a claude-code. The skill file lands at ~/.claude/skills/manus/SKILL.md.
What does the manus skill do?
It hands a task to the Manus agent over the API, tracks the run, and brings back the text plus any reports, CSVs or charts.
What does the manus skill need to run?
A MANUS_API_KEY environment variable. Calls go to https://api.manus.ai, and the agent profile is set in the request body.
Source text
SKILL.md · Apache-2.0
---
name: manus
description: Delegate complex, long-running tasks to Manus AI agent for autonomous execution. Use when user says 'use manus', 'delegate to manus', 'send to manus', 'have manus do', 'ask manus', 'check manus sessions', or when tasks require deep web research, market analysis, product comparisons, stock analysis, competitive research, document generation, data analysis, or multi-step workflows that benefit from autonomous agent execution with parallel processing.
license: Apache-2.0
metadata:
author: sanjay3290
version: "1.0"
---
# Manus
Manus is an autonomous AI agent that handles complex tasks asynchronously. Particularly strong at **deep research** with parallel processing, web browsing, and generating comprehensive reports with data visualizations.
## When to Use Manus
- **Deep research** - Market analysis, competitive landscaping, product comparisons
- **Stock/financial analysis** - Company research, technical analysis, price charts
- **Product research** - Feature comparisons across brands, specs analysis
- **Report generation** - Creates markdown reports, CSVs, charts, and visualizations
- **Multi-source synthesis** - Gathers and combines information from multiple websites
- **Long-running tasks** - Anything taking 1-10+ minutes of autonomous work
## Research Prompt Examples
Effective research prompts are specific about scope, sources, and desired output:
**Product comparison:**
```
Find the best 4K monitors for Mac with Thunderbolt connectivity and 120Hz+ refresh rate.
Focus on BenQ, Samsung, Dell, LG. Only include models released in the last year.
Compare specs, prices, and Mac-specific features. Output a comparison table.
```
**Stock/company analysis:**
```
Analyze [TICKER] stock: company profile, recent performance, technical indicators,
valuation metrics, and insider activity. Include a price chart for the past year.
```
**Market research:**
```
Research the [industry] market: key players, market size, growth trends,
recent developments, and competitive landscape. Focus on [region/segment].
```
**Competitive analysis:**
```
Compare [Product A] vs [Product B] vs [Product C]: features, pricing,
user reviews, pros/cons. Create a decision matrix for [use case].
```
## Environment Setup
Requires `MANUS_API_KEY` environment variable. Base URL: `https://api.manus.ai`
## Core Workflow
1. **Create task** → Returns `task_id` immediately
2. **Poll status** → Check until `status` is `completed` or `failed`
3. **Return results** → Extract output text and file attachments
## Creating a Task
```bash
curl -s -X POST "https://api.manus.ai/v1/tasks" -H "API_KEY:$MANUS_API_KEY" -H "Content-Type:application/json" -d '{"prompt":"<task description>","agentProfile":"manus-1.6"}'
```
**Agent Profiles:**
- `manus-1.6-lite` - Fast, simple tasks (quick lookups, simple questions)
- `manus-1.6` - Standard (default, good for most research)
- `manus-1.6-max` - Complex reasoning (deep research, multi-source analysis, detailed reports)
**Response:**
```json
{"task_id":"abc123","task_title":"...","task_url":"https://manus.im/app/abc123"}
```
## Checking Task Status
```bash
curl -s -X GET "https://api.manus.ai/v1/tasks/{task_id}" -H "API_KEY:$MANUS_API_KEY"
```
**Status values:** `pending`, `running`, `completed`, `failed`
Poll every 5-10 seconds until completed.
**Extract text output:**
```bash
curl -s -X GET "https://api.manus.ai/v1/tasks/{task_id}" -H "API_KEY:$MANUS_API_KEY" | jq -r '.output[] | select(.role=="assistant") | .content[] | select(.type=="output_text") | .text'
```
**Extract file attachments:**
```bash
curl -s -X GET "https://api.manus.ai/v1/tasks/{task_id}" -H "API_KEY:$MANUS_API_KEY" | jq -r '.output[] | select(.role=="assistant") | .content[] | select(.type=="output_file") | "\(.fileName): \(.fileUrl)"'
```
## Listing Tasks
```bash
curl -s -X GET "https://api.manus.ai/v1/tasks" -H "API_KEY:$MANUS_API_KEY" | jq '.data[] | {id, status, title: .metadata.task_title}'
```
## Multi-turn Conversations
Continue an existing task by including `taskId`:
```bash
curl -s -X POST "https://api.manus.ai/v1/tasks" -H "API_KEY:$MANUS_API_KEY" -H "Content-Type:application/json" -d '{"prompt":"follow-up question","taskId":"abc123","agentProfile":"manus-1.6"}'
```
## Delete a Task
```bash
curl -s -X DELETE "https://api.manus.ai/v1/tasks/{task_id}" -H "API_KEY:$MANUS_API_KEY"
```
## Advanced Options
| Parameter | Description |
|-----------|-------------|
| `taskMode` | `chat`, `adaptive`, or `agent` |
| `projectId` | Associate with project for shared instructions |
| `attachments` | Array of file objects (see below) |
| `connectors` | Pre-configured connector IDs (Gmail, Calendar, Notion) |
| `createShareableLink` | Enable public access URL |
## File Attachments
Attach files using one of three formats:
**URL attachment:**
```json
{"prompt":"Analyze this","attachments":[{"type":"url","url":"https://example.com/doc.pdf"}]}
```
**Base64 attachment:**
```json
{"prompt":"What's in this image?","attachments":[{"type":"base64","data":"<base64>","mime_type":"image/png"}]}
```
**File ID (after upload):**
```json
{"prompt":"Review this file","attachments":[{"type":"file","file_id":"file-xxx"}]}
```
## Projects
Create a project with shared instructions:
```bash
curl -s -X POST "https://api.manus.ai/v1/projects" -H "API_KEY:$MANUS_API_KEY" -H "Content-Type:application/json" -d '{"name":"My Project","instruction":"Always respond concisely"}'
```
Use project in task:
```bash
curl -s -X POST "https://api.manus.ai/v1/tasks" -H "API_KEY:$MANUS_API_KEY" -H "Content-Type:application/json" -d '{"prompt":"...","projectId":"proj_xxx","agentProfile":"manus-1.6"}'
```
## Best Practices
- Use `manus-1.6-lite` for simple queries (faster, cheaper)
- Use `manus-1.6` or `manus-1.6-max` for research tasks
- Always report `task_url` so user can view progress in browser
- Poll status with reasonable intervals (5-10s for simple, 15-30s for research)
- Check `credit_usage` field to track consumption
- For research: be specific about scope, timeframe, sources, and desired output format
- Research tasks typically produce multiple output files (reports, CSVs, charts) - extract all attachments
- Manus uses parallel processing for multi-faceted research - one prompt can cover multiple angles
## Error Handling
Check for failed tasks:
```bash
curl -s -X GET "https://api.manus.ai/v1/tasks/{task_id}" -H "API_KEY:$MANUS_API_KEY" | jq '{status, error}'
```
If `status` is `failed`, the `error` field contains the reason. Common issues:
- Invalid API key → Check `MANUS_API_KEY` is set
- Task timeout → Simplify prompt or use `manus-1.6-max`
- Rate limited → Wait and retry
## API Reference
For complete endpoint documentation, see [references/api.md](references/api.md).
© sanjay3290 · Apache-2.0 · sanjay3290/ai-skills