Skip to main content
Glama
geoffbelknap

LimaCharlie MCP

by geoffbelknap

lc_preview_feedback_simple_approval

Preview an external approval request to validate feedback content and configuration before sending.

Instructions

Preview sending an external approval request through ext-feedback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
oidYes
case_idNo
channelYes
questionYes
playbook_nameNo
denied_contentNo
timeout_choiceNo
timeout_contentNo
timeout_secondsNo
approved_contentNo
token_ttl_secondsNo
feedback_destinationYes
Behavior2/5

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

With no annotations, the description must bear the full burden of behavioral disclosure. It only says 'Preview sending,' which is ambiguous—it does not clarify if this action actually sends a request or simply simulates it. No information on permissions, side effects, or rate limits is provided.

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

Conciseness2/5

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

The description is a single short sentence, which is concise, but it is under-specified. It lacks essential details that should be included. True conciseness would provide adequate information in a compact form; this description sacrifices clarity for brevity.

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

Completeness1/5

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

The tool has high complexity (12 parameters) and no annotations or output schema, yet the description is only 8 words. It fails to explain what 'preview' entails, the purpose of the parameters, or what the tool returns. The description is wholly inadequate for an agent to use this tool correctly.

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 input schema has 12 parameters with 0% description coverage, and the tool description adds no explanation for any parameter. The parameter names alone (e.g., oid, channel, question) are insufficient for an agent to understand how to use them correctly. This is a critical deficiency.

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 action (preview sending) and the resource (external approval request via ext-feedback). The tool name also reinforces this. However, it does not explicitly differentiate from sibling preview tools for feedback (e.g., preview_feedback_acknowledgement, preview_feedback_question), which lowers the score slightly.

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?

No usage guidance is provided. The description does not indicate when to use this tool versus alternatives, nor does it mention any prerequisites or conditions. This is a significant gap given the number of sibling tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/geoffbelknap/limacharlie-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server