Create a developmental agent from a digital genome: {agent_name, purpose, initial_nodes (unique, >=1), fitness_metrics (>=1), optional growth_rules / safety_axioms}. Returns agent_id + initial graph summary.
| Name | Required | Description | Default |
|---|---|---|---|
| genome | Yes | ||
| request_id | No |
| 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 but only mentions creation and return values. It does not disclose side effects, authentication needs, or idempotency, leaving behavioral aspects unclear.
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 concise and front-loaded with the action, but the template format could be more structured (e.g., bullet points). Slightly above average.
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 and presence of an output schema, the description covers the key inputs and outputs. It omits error handling and validation details but is adequate for a creation 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 schema has 0% coverage and the genome property is an open object. The description compensates by specifying required fields (agent_name, purpose, initial_nodes, fitness_metrics) and optional fields (growth_rules, safety_axioms) with constraints like uniqueness and minimum count.
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 the tool creates a developmental agent from a digital genome, and lists required and optional fields. It is distinct from sibling tools like delete_agent or describe_agent.
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 is provided on when to use this tool versus alternatives, such as import_state or other creation methods. The description lacks usage 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.