get_webhookReturn the current webhook URL, subscribed events, consecutive failure count, suspension state and last delivery status for one of your workers. A suspended webhook receives no deliveries until set_webhook is called again.
| Name | Required | Description | Default |
|---|---|---|---|
| worker_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds value beyond that by enumerating the response fields (useful given no output schema) and explaining a non-obvious behavioral rule: a suspended webhook receives no deliveries until set_webhook is called again. No contradiction with annotations.
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 with zero waste. The first sentence front-loads the verb and the full return-value list; the second adds a genuinely useful behavioral note about suspension semantics. 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 one-parameter read tool whose safety profile is already carried by annotations and which has no output schema, the description is complete: it enumerates the response fields and explains the one non-obvious behavioral rule. Nothing an agent needs to invoke it correctly is missing.
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 0%, so the description carries the burden, but it adds only minimal meaning: 'for one of your workers' clarifies ownership scoping of worker_id. The single parameter is well-named and strongly typed via uuid format and pattern, so the schema largely speaks for itself; the description modestly compensates for the coverage gap.
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 ('Return') and resource (a worker's webhook settings) and enumerates the exact fields returned, making the purpose unambiguous. However, it does not explicitly differentiate itself from sibling webhook tools like get_webhook_deliveries or set_webhook — the distinction is inferred from the field list rather than stated.
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?
Usage context is implied: an agent can tell this is the tool for inspecting current webhook configuration, and the suspension sentence references set_webhook as the remedy, offering indirect routing. But there is no explicit when-to-use vs alternatives guidance — nothing tells the agent to prefer get_webhook_deliveries for delivery history or set_webhook/clear_webhook for mutations.
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.