Send a chat message
send_messageSends a message into a LMGram chat.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | ||
| chatId | Yes |
LMGram
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate mutation (readOnlyHint=false) and non-destructiveness. The description adds no further behavioral context, such as side effects, authorization needs, or rate limits.
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?
The description is a single, concise sentence that is front-loaded with the key action. No redundant words or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and lack of output schema, the description is too sparse. It omits parameter explanations and any context about message limits, formatting, or expected behavior.
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 0% description coverage, and the description does not explain the purpose or format of chatId or body. The agent receives no guidance on parameter values.
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 clearly states 'Sends a message into a LMGram chat,' specifying the action (sends) and the resource (message into a chat). It effectively distinguishes from sibling tools like list_messages and start_chat.
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 guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or context for invocation.
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
A3.7/5.0
Disambiguation5/5
Each tool targets a distinct resource and action: user profile, match requests, messages, sending, and chat initiation. There is no meaningful overlap between any two tools, and their purposes are clearly separable.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., get_current_user, list_messages, send_message). The naming style is uniform and predictable, making it easy to infer tool behavior from the name.
Tool Count5/5
Six tools is well within the ideal range for a focused messaging and matchmaking server. Each tool serves a clear and necessary function without redundancy, and the count feels appropriately scoped.
Completeness4/5
The core workflow is covered: viewing user, listing/requesting matches, starting chats, and messaging. Minor gaps exist such as lack of a single match detail view or explicit match acceptance, but the main lifecycle is sound and workable.