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zebbern

agloop-mcp

by zebbern

agloop_get_agent_info

Retrieve the full agent prompt and frontmatter from an agent's definition file by providing the agent name.

Instructions

Read the definition file (.agent.md) for a specific agent. Returns the full agent prompt including frontmatter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations exist, so the description carries the burden. It states 'Read' and 'Returns the full agent prompt', indicating a non-destructive read operation, but it does not explicitly confirm idempotency or side-effect-free behavior.

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

Conciseness5/5

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

Two sentences, front-loaded with the action, no wasted words. Efficiently conveys the tool's function.

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?

The description explains the return value (full prompt including frontmatter) and with an output schema present, completeness is decent. However, it lacks error conditions or prerequisites, which is a gap for a tool with no annotations.

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?

With 0% schema description coverage, the description should compensate but only vaguely mentions 'for a specific agent'. It does not provide format, constraints, or examples for the agent_name parameter.

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

Purpose5/5

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

The description uses a specific verb 'Read' and clearly identifies the resource as the definition file (.agent.md) for an agent. It distinguishes from siblings like log or task tools by focusing on agent definition retrieval.

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

Usage Guidelines3/5

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

The description implies usage for reading agent info but does not explicitly state when to use this tool vs alternatives like agloop_get_state or others. No exclusion criteria or context provided.

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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