Full current state: genome, cognitive graph (nodes/edges with weights and trust), and summary counts.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that the tool returns genome, cognitive graph, and summary counts, which implies read-only behavior. However, it does not mention potential performance impact (e.g., large graph size) or any constraints like recency of state.
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 a single sentence that front-loads 'Full current state' and lists key components. It is concise with no redundant information, though listing items in bullet form could improve skimmability.
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?
Given the complexity of the state and the presence of an output schema (not shown), the description provides adequate high-level coverage of return content. However, it lacks details on error handling, such as behavior when agent_id does not exist, and does not contrast with the similar describe_agent sibling.
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 must compensate for parameter meaning. The description does not mention the agent_id parameter at all, leaving the agent to rely on the parameter name alone. Although agent_id is self-explanatory, the description should explicitly state it is required and perhaps advise on format or source.
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 that the tool returns the full current state including genome, cognitive graph with nodes/edges/weights/trust, and summary counts. This distinguishes it from sibling tools like describe_agent (likely a summary) and export_state (for serialization).
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?
No guidance on when to use this vs alternatives. There is no mention of when to prefer get_agent over describe_agent, export_state, or list_agents. An agent may need to infer usage from context.
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 have clearly distinct purposes, but describe_agent and get_agent both return agent information, and best_next_steps vs route_task could be confused in decision-making contexts. The descriptions help clarify, so the ambiguity is limited.
The vast majority of tools follow a verb_noun snake_case pattern (e.g., create_agent, list_agents), but best_next_steps breaks the pattern and compute_efficiency_report reads as a noun phrase. These are minor deviations from an otherwise consistent style.
With 14 tools, the server sits comfortably within the ideal 3-15 range. Each tool serves a specific function in the agent lifecycle or compute-routing workflow, so the count feels well-scoped without unnecessary bloat.
The agent lifecycle is well covered with create, delete, get, list, describe, export/import, evaluation, and ledger access. The compute side includes profile registration, task routing, outcome recording, and reporting. Minor gaps like no direct agent update or profile listing exist, but they are workable.