comment_on_requestAdd the signed-in customer's comment to a thread — their workaround, their trade's angle, their +1 with a reason. Requires authorization.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The thread id | |
| body | Yes | The comment |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as a write operation (readOnly=false), so the description's added value is mainly 'requires authorization'. It does not describe whether repeated calls create duplicate comments or how the comment is attached to the thread, though idempotentHint=false partially covers the duplicate concern.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler. The verb, object, content guidance, and authorization requirement are all present and front-loaded, with every clause contributing useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter mutation with full schema coverage, the description plus annotations is largely adequate: purpose, target thread, comment content, and authorization are covered. The only real gap is explicit routing guidance against sibling tools, which was already penalized under usage guidelines.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes both parameters, giving a baseline of 3. The description adds value by indicating what the body should contain — a workaround, a trade angle, or a +1 with a reason — which helps an agent compose a meaningful comment beyond the schema's generic 'The comment'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: adding the signed-in customer's comment to a thread. The examples ('workaround', 'trade's angle', '+1 with a reason') make the action clear, but it does not explicitly contrast with sibling tools like heart_request or post_feature_request, so it is slightly short of full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The examples imply the intended use case: a customer commenting on an existing request, including a reasoned +1. However, there is no explicit statement of when not to use this tool or when to prefer a sibling such as heart_request for a simple endorsement, leaving the guidance implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools map to a clear resource/action, but get_product_overview and search_knowledge_base both claim to answer 'does it do X', and search_forum and get_roadmap both surface statuses, so an agent could pick the wrong one. The descriptions reduce the ambiguity but do not fully eliminate it.
The set uses lower_snake_case and broadly follows a verb_noun shape with get_/search_ prefixes for reads. However, my_requests and server_info are noun phrases and comment_on_request inserts a preposition, so the pattern is not perfectly uniform.
At 13 tools, the count is well within a reasonable range for the scope: product info, pricing, forum search/read/write, hearts/comments, waitlist, contact, and personal status. Each tool covers a distinct interaction area and none feels redundant enough to cut.
The surface covers the main customer journeys: learn about the product, search/read forum, post/comment/heart, check personal requests, ask for contact, and join the waitlist. Minor gaps exist (e.g., no edit/delete for comments or a way to check waitlist status), but agents can complete core workflows without dead ends.