athena_causal_identify_extended

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

No annotations exist, so the description must disclose behavioral traits. It only adds that results depend on graph/observed-node/assumption correctness, which is a useful validity caveat, but doesn't mention read-only behavior, side effects, output structure, or error conditions.

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 and front-loads 'Perform', but it is under-specified for a 10-parameter tool. No structured breakdown of criteria or key parameters is provided.

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?

With no annotations, no output schema, and 10 parameters, this one-sentence description is far from complete. It omits how to specify the DAG, what method values are valid, and what the tool returns.

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 input schema has 10 parameters with 0% schema description coverage, yet the description names none of them explicitly. Terms like 'supplied-DAG' and 'observed-node' only weakly hint at edges/observed_nodes, leaving method, treatment, outcome, mediators, instruments, assumptions, and max_adjustment_size unaddressed.

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 it performs conditional identification on a supplied DAG for backdoor, frontdoor, or instrument criteria, giving a specific verb and resource. It doesn't explicitly distinguish this 'extended' variant from the sibling athena_causal_identify, but the criteria list provides some scope clarity.

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 given on when to choose this over athena_causal_identify or other causal tools. The caveat about results depending on correctness is a validity note, not usage direction.

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