Record a specialist sub-agent brief and output for an existing Hermes task run. Requires x-agent-key and task ownership.
| Name | Required | Description | Default |
|---|---|---|---|
| brief | Yes | ||
| output | Yes | ||
| status | No | ||
| confidence | No | ||
| task_run_id | Yes | ||
| subagent_name | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It does mention the authorization requirement ('x-agent-key and task ownership') and the existence constraint, which is useful. However, it does not disclose side effects (e.g., append vs overwrite) or the response shape, leaving some behavioral ambiguity.
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 concise, front-loaded sentences. The first sentence states the action and resource; the second covers prerequisites. Every clause serves a purpose and there is no redundancy.
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?
The tool has 6 parameters, including two nested objects (brief and output) with no defined structure, and no output schema. The description does not explain the structure of these objects, the allowed values for status/confidence, nor the return behavior. This leaves too many gaps for an agent to confidently invoke the tool.
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?
The description maps core parameters to its language: 'brief' and 'output' relate directly to the sub-agent's brief and output, 'existing Hermes task run' maps to task_run_id, and 'sub-agent' points to subagent_name. It provides no meaning for status or confidence, and with 0% schema description coverage, this partial compensation is notable but incomplete.
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+resource: 'Record a specialist sub-agent brief and output for an existing Hermes task run.' This clearly states the tool's function and distinguishes it from sibling tools like record_reflection or report_skill_outcome by focusing on sub-agent traces.
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 provides clear context: it is for existing task runs and requires x-agent-key and task ownership. However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of full usage guidance.
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 task-run and record_* tools are clearly distinct, but query_lessons, query_lessons_full, and query_lessons_premium all describe nearly the same underlying lesson-query action separated mainly by access tier and payment. An agent can easily call the wrong one, especially because 'full' and 'premium' boundaries are unclear.
The tools consistently use snake_case verb_noun names such as start_task_run, complete_task_run, record_reflection, and submit_incident_report. The query_lessons variants use a predictable suffix pattern, and there is no mixing of naming conventions.
Ten tools is a reasonable footprint, but the three query_lessons variants are essentially reimplementations of the same query by payment/access tier. The count is not excessive, though it could be reduced without losing real capability.
The set covers task-run start/completion and lesson querying, but there is no way to read back task runs, reflections, subagent traces, or usage records after submitting them. This makes the task-run side feel mostly write-only and creates a notable gap in a memory-focused server.