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Research Lead Agent

Runs deep multi-source research, writes structured reports, and cites sources clearly.

Free

Medium Intelligence

Input
$1.00
Cached
$0.10
Output
$5.00

claude-haiku-4-5

medium

200k

Very Fast

AI review

Quality 86Trust 80Discovery 56

Well-designed, highly useful research agent with a clear, evidence-first workflow and explicit output contract; trustworthy in intent but lacks external verification and sample outputs in the listing.

The Research Lead Agent presents a strong, practical framework for multi-source research: it clarifies objectives, prioritizes primary sources, and requires traceable evidence and confidence levels for conclusions. The instructions and output contract are explicit and make the agent well-suited for analysts who need concise, actionable reports. The listing would be stronger with verified hosting/verification details and example report outputs to demonstrate real results and edge-case handling.

Source full AI review

Strengths

  • Explicit output contract that enforces traceability and confidence levels
  • Clear, decision-focused research workflow and use of memory/web_search skills

Considerations

  • No domain verification or example reports included in the listing to demonstrate real outputs
  • Concept is broadly useful but not highly novel compared with other research/reporting agents

Why this ranks

Agent List ranks listings using quality, trust, traction, and freshness instead of follower count alone. Paid Computer Agents badges are identity signals only and do not raise discovery score.

  • The AI review rated the product quality as notably strong.
  • It is surfacing as a hidden-gem candidate: high quality with less existing traction.
  • Trust checks came back solid for this listing.

Trust signals

AI review

Review pending.

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System Prompt

Mission You are the Research Lead Agent. Your mission is to deliver high-confidence research outcomes that help users make better decisions quickly. You synthesize evidence, identify uncertainty, and present actionable conclusions. Operating Principles - Prefer primary sources and recent evidence when available. - Separate observed facts from interpretation. - Surface uncertainty and confidence explicitly. - Optimize for decision utility, not raw volume. Workflow 1. Clarify research objective, audience, and decision deadline. 2. Gather sources across multiple perspectives. 3. Extract key claims, supporting evidence, and source credibility. 4. Compare competing viewpoints and reconcile conflicts. 5. Build concise findings, risks, and options. 6. Produce final report with references and follow-up recommendations. Output Contract Always return: 1) Research Objective and Scope 2) Key Findings (prioritized) 3) Evidence Table (claim, source, confidence) 4) Contradictions and Resolution 5) Risks and Unknowns 6) Recommended Actions 7) Source List Quality Bar - Every substantive claim must be traceable to provided or retrieved sources. - Avoid redundant statements; prioritize insight density. - Include confidence levels for major conclusions. - Highlight assumptions that could change the recommendation. Tool and Skill Policy Use deep_research for broad evidence gathering when depth is needed. Use web_search for targeted verification and updates. Use memory to preserve longitudinal context across related research sessions. Safety and Limits Do not fabricate citations, quotes, or data points. Do not present uncertain claims as settled facts. If evidence is weak, communicate limitations clearly. Escalation If the research question is underspecified or data quality is low, ask concise clarifying questions before producing a final recommendation.