complex-research

Delegates multi-source research tasks to specialized research agents with structured prompts.

Updated Aug 1, 2026
One-click install
npx skills add https://github.com/siegenthalerroger/.llmctl-marketplace --skill complex-research-siegenthalerroger
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: complex-research
Source: https://github.com/siegenthalerroger/.llmctl-marketplace/tree/main/plugins/llmctl-core-0.4.0/skills/complex-research
Command: npx skills add https://github.com/siegenthalerroger/.llmctl-marketplace --skill complex-research-siegenthalerroger

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Complex research tasks that require investigating many sources can flood the main conversation with redundant fetches and wasted tokens. This Skill defines when and how to delegate such investigations to a research subagent, and how to trust its results without re-querying the same sources. ## Core Features & Use Cases - Delegation Thresholds: Clear criteria for when to delegate (3+ sources, synthesis, comprehensive coverage) versus when to answer directly with a single lookup. - Subagent Result Authority: Rules that treat subagent output as authoritative, preventing redundant re-fetching of URLs, repositories, and documentation. - Prompt Structuring Guidance: A template for writing self-contained research prompts with objectives, scope, sources, deliverables, and success criteria. - Use Case: When evaluating which authentication library to adopt, delegate a research agent to compare official docs, GitHub repos, and community discussions, then receive a comparison table and recommendation without re-checking any source yourself. ## Quick Start Ask the assistant to research and compare three logging frameworks for your project by delegating to a research agent with defined sources and deliverables.

Frequently Asked Questions about complex-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
When should I delegate research to a subagent instead of searching myself?▼

Delegate when the task needs three or more distinct sources, synthesis of alternatives, comprehensive topic coverage, or documentation generation. Simple factual lookups answerable with one tool call should be handled directly without delegation.

How do I write an effective research subagent prompt?▼

Include a clear objective, scope boundaries, specific sources or repositories to investigate, the expected output format such as a report or comparison table, and success criteria. Vague requests without source guidance or deliverables produce poor results.

Should I re-fetch sources a research subagent already checked?▼

No. Treat subagent results as authoritative and complete. Re-fetching the same URLs, repositories, or documentation wastes tokens without adding information. If results seem insufficient, improve the original prompt instead.

What tasks should not be delegated to a research agent?▼

Do not delegate simple factual lookups, searches within the current workspace only, questions with direct answers in immediate context, or tasks where you already have sufficient information to proceed.

Why are my research subagent results incomplete or shallow?▼

Insufficient results usually indicate an underspecified prompt rather than missing data. Add explicit sources, depth requirements, deliverable structure, and context about how the findings will inform a decision or implementation.