delete_workerHard-delete a worker. Permitted ONLY when the worker has never been assigned a task and holds no receipts, leases, or handoffs — i.e. it was created by mistake. Anything with history returns 409 and must be retired with archive_worker instead, so the audit trail survives.
| Name | Required | Description | Default |
|---|---|---|---|
| worker_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already set destructiveHint=true and readOnlyHint=false, and the description adds crucial behavior beyond that: deletion is hard/permanent, it is rejected with 409 if any history exists, and the reason is to preserve the audit trail via archive_worker. This clearly communicates the destructive semantics and consequence of misuse.
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 compact and front-loaded: the core action ('Hard-delete a worker') comes first, followed immediately by the precondition, error behavior, and alternative. Every sentence carries necessary information and there is no fluff.
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 destructive single-parameter tool with no output schema, the description covers the action, the exact precondition, the failure mode, and the fallback tool. An agent has everything needed to decide when to call this and what to expect on rejection.
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 for parameter meaning, but it never mentions worker_id. The parameter name and UUID format are fairly self-evident, yet the description adds no parameter-specific guidance such as how to obtain the ID or what values are valid. With only one parameter this is a minor gap, but the burden was not met.
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 opens with a specific verb and resource: 'Hard-delete a worker.' It also distinguishes itself from archive_worker by stating that workers with history must be retired instead, so an agent can clearly identify this as the permanent, history-free deletion path.
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 explicitly states when this tool is permitted ('only when the worker has never been assigned a task and holds no receipts, leases, or handoffs'), when it is not ('Anything with history returns 409'), and names the exact alternative ('must be retired with archive_worker instead'). This is actionable routing guidance with no ambiguity.
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.