list_open_questionsList questions raised on tasks you can see, with any human answers. Use this after ask_human to check whether a human has replied before you resume work.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| task_id | No | Limit to one task id. | |
| include_answered | No | Include already-answered questions. Default false. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims the list comes 'with any human answers,' but include_answered defaults to false, meaning answered questions are excluded by default. This can mislead an agent about what the tool returns. Annotations cover read-only safety, but the description does not clarify the open-question filtering behavior.
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 tight sentences with no filler; the core action is front-loaded and the usage guidance is immediate.
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 read-only listing tool this covers purpose and a concrete workflow, but the default exclusion of answered questions is only recoverable from the schema. Without an output schema, the description should be unambiguous about what is returned, and it currently is not.
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 descriptions already cover task_id and include_answered; limit has type/min/max but no prose meaning. The description adds no parameter-level detail and doesn't clarify how limit applies, so it neither compensates for the missing limit description nor conflicts with the schema.
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?
Uses a specific verb ('List'), names the resource ('questions raised on tasks you can see'), and states that it returns human answers. The 'after ask_human' context clearly separates it from the asking/answering siblings.
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?
Explicitly instructs agents to call this after ask_human to poll for a human reply before resuming work. It does not name explicit alternatives or when-not-to-use scenarios, so it stops short of 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.
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.