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reasoningdelegationmedium

The medium-effort reasoning agent is designed to handle moderate to complex tasks by applying structured, multi-step thinking and deeper analysis. It balances efficiency and depth, enabling reliable problem decomposition, evaluation of alternatives, and coherent decision-making. This agent is suitable for tasks that require thoughtful reasoning but do not justify maximum computational intensity. Expected Runtime: ~50s.

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

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It goes beyond the name by disclosing expected runtime (~50s) and describing the reasoning approach (problem decomposition, evaluation of alternatives, coherent decision-making). However, it does not disclose output shape, failure modes, or whether the reasoning result is deterministic, leaving meaningful gaps for a zero-annotation tool.

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 efficiently written — two sentences that front-load the tool's identity and purpose, followed by the runtime signal. No wasted words or filler. The expected runtime line earns its place as a practical cost indicator. Slightly more structure (e.g., separating purpose from usage) could improve scannability but is not necessary.

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?

An output schema exists and no nested objects are involved, so return value documentation is partially offloaded. However, the definition's main gap is the undefined task parameter semantics and missing guidance on how detailed the input should be, which is critical for a delegating tool. The complexity is moderate and useful context is present, but the input contract is underspecified, keeping this at a 3.

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

Parameters2/5

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

Schema description coverage is 0% — the task parameter's description is empty. The description implies the payload includes a task ('handle moderate to complex tasks') but never specifies what a good task string should contain, its expected granularity, or formatting. With a single crucial parameter and zero schema coverage, the description should compensate far more than it does.

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 this is a 'medium-effort reasoning agent' handling 'moderate to complex tasks' with structured multi-step thinking, which distinguishes it from reasoningdelegationhigh and reasoningdelegationlow by effort tier. The verb+resource is reasonably clear (delegate reasoning at medium intensity), though it doesn't crisply define what the agent physically returns or produces, so it falls just short of a 5.

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

Usage Guidelines4/5

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

Provides explicit suitability guidance: 'suitable for tasks that require thoughtful reasoning but do not justify maximum computational intensity,' which tells the agent when this tier fits relative to the high/low siblings. The ~50s expected runtime offers a cost signal. It lacks explicit exclusions or named alternatives, but the effort-tier framing makes the when-to-use decision reasonably inferable.

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.

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