answer_questionAnswer an open question raised on a task. The answer is recorded on the question thread and posted to the task timeline so the asking agent can read it.
| Name | Required | Description | Default |
|---|---|---|---|
| answer | Yes | Your answer. | |
| question_id | Yes | Question id from list_open_questions or get_task. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a meaningful behavioral trait beyond the annotations: the answer is recorded on the question thread and posted to the task timeline. This explains side effects and audience. It aligns with readOnlyHint=false and destructiveHint=false, with no contradiction. It doesn't discuss failure modes, permissions, or idempotency, but the stated effects are valuable.
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 two sentences and 31 words. It front-loads the core action in the first sentence, then adds the critical side effects in the second. There is no redundancy, tautology, or fluff; every word earns its place.
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 2-parameter write operation with no output schema, the description explains the primary flow: answer recorded, posted to timeline, readable by the asking agent. It does not mention response/confirmation behavior or any preconditions, but the schema covers parameter sourcing. Slightly more could be said about what happens after posting, but overall it is nearly complete.
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 description coverage is 100%: both answer and question_id have descriptive schema entries, including the origin of question_id ('from list_open_questions or get_task'). The tool description adds no additional parameter-level meaning, so a baseline 3 is appropriate because the schema already carries the semantic load.
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 clearly states the tool's function: 'Answer an open question raised on a task.' It also specifies the distinct side effects (recorded on question thread, posted to timeline) that set it apart from generic comment tools. It lacks an explicit comparison to sibling tools, but the 'open question' phrasing and effect descriptions provide reasonable 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 description implies when to use it: when an open question exists on a task (especially 'so the asking agent can read it'). However, it provides no explicit alternative guidance, such as when to use add_comment or reply_to_support_request instead, or any conditions that would exclude use. The usage context is clear but under-specified relative to the sibling set.
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 target a distinct resource and action, but several adjacent pairs are easy to confuse: add_comment vs add_progress_note, call_executor vs call_integration, log_client_decision vs update_client_context vs memory_save, and list_context_sources vs list_integrations. The descriptions do disambiguate them, but the boundaries are subtle enough that misselection is likely with 81 tools.
The overwhelming majority follow a clear verb_noun snake_case pattern (create_task, update_project, list_integrations, set_webhook), and get_/ list_/ create_/ update_ families are predictable. Minor deviations exist: memory_read/memory_save/memory_search invert to object_verb, and bare nouns like whoami, glossary, and security_posture break the pattern, but there is no chaotic casing or mixed conventions.
At 81 tools, this is far above the weight that is comfortable for an agent's tool-selection surface, especially since many tools belong to families that could be consolidated (webhooks, worker keys, project logs, context/memory). Although the domain is broad, the count will overwhelm agents and increase misrouting.
The surface is unusually comprehensive: tasks, projects, workers, leases, artifacts, comments, handoffs, webhooks, keys, context, memory, integrations, and support all have create/read/update/delete or equivalent lifecycle coverage. The gaps are minor, such as remove_dependency without a visible add_dependency and no artifact/comment deletion, but agents can work around them.