autonomous_varrd_ai

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds behavioral context beyond annotations: it mentions the tool draws from knowledge graphs, generates novel hypotheses, returns complete results (edge or not, stats, trade setup), and costs ~$0.25 per call. Annotations already indicate non-readOnly and openWorld, and the description aligns with these without contradiction.

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 (about 150 words), well-structured with a clear opening, a 'BEST FOR' highlight, and a direct comparison with the sibling tool. Every sentence adds value; no fluff or repetition.

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 tool's complexity (6 parameters, 1 required, 2 enums) and the presence of an output schema, the description is complete. It covers purpose, usage, output, cost, and alternatives. The output schema handles return value details, so the description need not repeat them.

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 coverage is 100%, so baseline is 3. The description adds value by providing concrete examples (e.g., 'momentum on grains') and explaining how parameters like test_type and search_mode affect behavior. This contextualizes the parameters beyond their schema descriptions.

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's purpose: 'Point VARRD's autonomous AI in a direction and let it discover edges for you.' It specifies the action (exploring), resource (VARRD knowledge graph), and outcome (novel hypotheses). It also distinguishes from the sibling tool 'varrd_ai' by explicitly stating when to use each.

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 explicit when-to-use guidance: 'BEST FOR: Exploring a space broadly.' It also tells when not to use it and what alternative to use: 'Use varrd_ai instead when YOU have a specific idea to test and want full control over each step.' This is clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.