Answer a thread's clarifying questions (status must be awaiting_answers).
`answers` is a list of {"idx": <int from get_request_status>, "answer_md":
<str, 1..2000 chars>}. Answer EVERY question exactly once. Flips the thread
back to intake_pending; poll get_request_status again.
| Name | Required | Description | Default |
|---|---|---|---|
| answers | Yes | ||
| thread_id | Yes | ||
| project_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate a non-read-only mutation (readOnlyHint=false). Description adds the state transition ('Flips the thread back to intake_pending') and the requirement to answer every question exactly once, which is useful beyond annotations. Could mention failure modes, but sufficient.
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?
Two sentences plus a parameter spec, all high-value. Front-loaded with purpose and precondition, no wasted words.
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?
Given output schema exists (return value not needed) and moderate complexity, the description covers purpose, precondition, parameter details, and post-condition. It is complete for an agent to invoke correctly.
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?
Schema has 0% description coverage, so the description must carry the load. It fully explains the `answers` structure with idx source and character limits, and clarifies the 'every question exactly once' rule. project_id and thread_id are self-explanatory.
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?
Description states a specific verb+resource: 'Answer a thread's clarifying questions' with a clear precondition (status must be awaiting_answers). It distinguishes from siblings like submit_request (new) and get_request_status (polling) by focusing on the answering action.
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?
Provides explicit context: must be in awaiting_answers status, and instructs to poll get_request_status after. It implies when to use (when questions are pending) but lacks explicit when-not or alternatives, so not a full 5.
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.
Every tool targets a distinct resource and action duo, even within clusters like request handling or security reviews. The get_ vs run_ pairs are clearly separated, and descriptions explicitly contrast confusing alternatives such as archive_project vs delete_project.
The set overwhelmingly follows verb_noun snake_case (submit_request, list_projects, resolve_escalation). The one visible deviation is project_status, which breaks the get_/pattern, and signup is a single-word verb instead of sign_up.
37 tools is well above the 25+ threshold and spans auth, billing, project lifecycle, roadmap, escalations, product documents, and multiple review types. Most tools earn their place, but the surface is too large for one server and would be more coherent split into focused servers.
The domain coverage is broad: full project lifecycle, request intake/refinement, roadmap manipulation, escalation handling, product doc read/write, and security/legal review flows. Minor gaps exist, most notably no dedicated task-listing or task-update tool, but agents can work around these via project_status and list_escalations.