athena_latent_project_admg

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

With no annotations provided, the description carries the full burden. It does disclose the algorithmic mechanism ('using latent-only internal directed paths/common latent ancestors') and the output type ('restricted observed ADMG'), which adds useful context. However, it does not mention side effects, return format, or whether the input is mutated, leaving behavioral traits partially undisclosed.

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 two sentences, front-loaded with the core action, and the final 'Not data discovery' is a useful clarification. Every word earns its place; there is no waste.

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 operation and the absence of an output schema, the description gives a precise definition of the transformation but does not describe the return value structure, error conditions, or edge cases. It is adequate for a domain expert but not fully complete for an automated agent without prior knowledge of ADMG projection.

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%, and the description does not explicitly map parameters. It implies meanings (causal DAG → edges, explicit latent nodes → latent_nodes, observed ADMG → observed_nodes) but does not provide detailed semantics or format guidance. The description adds only implicit meaning, not enough to compensate for the complete lack of 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 states a specific action ('Project a supplied causal DAG with explicit latent nodes into a restricted observed ADMG') with a clear resource and outcome. It also distinguishes itself from data discovery methods by explicitly stating 'Not data discovery,' which differentiates it from sibling tools like athena_pag_candidate_discover or athena_fci_lite_discover that perform data-driven discovery.

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 a clear context of when to use the tool (when you have a causal DAG with latent nodes and need an observed ADMG) but does not explicitly name alternatives or exclusions beyond 'Not data discovery.' It lacks explicit guidance on when NOT to use this tool in favor of another, so it gives partial guidance but not full usage clarity.

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