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scientificresearchagent

Analyzes tasks, questions, or problems strictly from a scientific perspective. Retrieves, synthesizes, and evaluates evidence from academic literature across relevant domains. Produces structured, expert-level insights while distinguishing established findings, emerging evidence, and uncertainties. Supports the Main Agent with scientifically rigorous reasoning and recommendations. Expected Runtime: ~60s.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payloadYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses an expected runtime of ~60s and the output nature (structured, expert-level insights), which is helpful. However, it does not mention any side effects, data access requirements, or limitations, leaving gaps in behavioral transparency for a tool with no annotation support.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with the core purpose stated in the opening sentence and supporting details in two more sentences. The runtime note is useful. No redundant information is present, and the structure flows logically from purpose to capabilities to expected behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description covers the tool's purpose and provides a runtime estimate, it omits essential context about the input parameter. With zero parameter description coverage and no guidance on usage boundaries, the description is not complete enough for an agent to correctly invoke this tool. The presence of an output schema partially compensates for return-value documentation, but the input semantic gap remains.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'task_description' has an empty description in the schema (coverage 0%), and the tool description offers no additional guidance on how to formulate the task description. The agent receives no semantic information about this parameter, making it impossible to know what content or format is expected. This is a critical gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Analyzes' and the resource 'tasks, questions, or problems', and specifies the scientific perspective and academic literature focus. It distinguishes itself from generic research agents by emphasizing 'distinguishing established findings, emerging evidence, and uncertainties', though it does not explicitly name a sibling alternative, leaving some ambiguity against 'researchagent'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies scientific use cases ('strictly from a scientific perspective', 'academic literature') but provides no explicit when-to-use versus when-not-to-use guidance. It does not reference any sibling tools or exclusions, leaving the agent to infer when this specialist is appropriate over the many other available agents.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

C2.7/5.0
Disambiguation3/5

Several tools overlap in purpose, particularly the research/analysis agents (constructivecritic, firstprinciplesanalyst, scientificresearchagent, researchagent) and the three reasoningdelegation agents, which differ only by effort level. Some tools like 'exploitagent' and 'testagent' have vague descriptions that don't clarify distinct roles. However, many tools are clearly distinct (e.g., campbuddy vs. smart_fridge___nutrition), and the core router tools (discover_agents, a2a_call_agent, wait_for_task) are well-defined.

Naming Consistency2/5

Naming is inconsistent: some tools use snake_case (a2a_call_agent, discover_agents, wait_for_task) while most others are camelCase or concatenated lowercase (browsernavigationagent, campbuddy, reasoningdelegationhigh). There's also odd naming like 'smart_fridge___nutrition' with triple underscore, and simple names like 'testagent' and 'exploitagent'. No consistent convention exists across the set.

Tool Count4/5

With 24 tools, this is near the upper limit but still reasonable for an agent router that hosts many pre-defined specialized agents. The core router functions (discover, call, wait) are supplemented by a diverse set of agent tools. It's borderline heavy but each tool represents a distinct agent or action, so it's acceptable.

Completeness4/5

The router functionality is well-covered: discovery (discover_agents), synchronous calling (a2a_call_agent), asynchronous handling (wait_for_task), and skill lookup (search_skills/get_skill) for extension. Missing are explicit cancellation or task management tools, but core workflows are supported. The presence of domain-specific agents (campbuddy, silpo_home_restaurant) doesn't detract from router completeness.

Resources