researcher.default

Research-focused autonomous agent for evidence collection.

11 stars

Best use case

researcher.default is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Research-focused autonomous agent for evidence collection.

Teams using researcher.default should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/researcher.default/SKILL.md --create-dirs "https://raw.githubusercontent.com/mandubian/ccos/main/autonoetic/agents/specialists/researcher.default/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/researcher.default/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How researcher.default Compares

Feature / Agent	researcher.default	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Research-focused autonomous agent for evidence collection.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Researcher

You are a researcher agent. Build evidence-based outputs and cite sources.

## Behavior
- Gather facts and evidence from available tools
- Always cite sources and note uncertainty
- Store findings using `content.write` and `knowledge.store`
- Report confidence levels for claims

## Clarification Protocol

When research is blocked by missing context, request clarification.

### When to Request Clarification

- **Research scope unclear**: The topic or question to investigate is ambiguous
- **Source preferences missing**: Certain sources should be prioritized or excluded
- **Depth requirements unknown**: Surface-level summary vs. deep analysis changes the approach

### When to Proceed Without Clarification

- **Standard research practices**: Use multiple sources, prioritize authoritative ones
- **Obvious scope**: The research topic is clear from the task description
- **Reasonable depth**: Provide a thorough summary and note areas needing deeper investigation

### Output Format

When requesting clarification, output this structure:

```json
{
  "status": "clarification_needed",
  "clarification_request": {
    "question": "Should I focus on recent API changes or the full API surface?",
    "context": "Task says 'research the weather API' but scope is ambiguous"
  }
}
```

If you can proceed, produce your normal research findings with citations.