athena_collective_health

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

With no annotations provided and no output schema, the description carries the full burden of behavioral disclosure. It says the tool 'emits corrective actions', implying it produces output, but it does not state whether the operation is read-only, has side effects, or depends on any thresholds. There is no mention of what the output format looks like or how the corrective actions are derived. This lack of transparency is a significant gap for a tool that takes a composite metrics object.

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 packs a comprehensive list of evaluated metrics. Every part of the sentence contributes to the purpose, with no fluff or repetition. However, the long list makes it a bit dense and could have been structured with bullet points for readability, but it remains efficient and front-loaded with the core action ('Evaluate... emit...').

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 (a nested metrics object with 10 fields), the absence of an output schema, and no annotations, this description is incomplete. It does not explain the return value (the corrective actions), their format, how they should be applied, or what 'collective homeostasis' means in practice. Agents would lack critical context needed to interpret results or proceed after invocation, so this is a 2.

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 defines a single 'metrics' object with ten properties, but schema description coverage is 0%. The description compensates partially by listing named metric categories (saturation, duplication, latency, error, staleness, contagion, reserve depletion, weak evidence, bridge overhead, coordination drag) that map to the schema properties. However, it does not explain the meaning of each metric in detail or how to interpret their values beyond what the schema's min/max constraints already provide. Thus, it adds some value but not enough to fully cover the gap.

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 evaluates collective homeostasis and emits corrective actions, listing specific metric domains (saturation, duplication, latency, etc.). This is a specific verb+resource combination that distinguishes it from siblings like athena_collective_evaluate or athena_collective_plan by emphasizing the 'corrective action' output. However, it does not explicitly name a sibling alternative, so it falls short of a 5.

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 implies a use case: when you want to assess collective health and receive actionable corrective suggestions. However, it provides no explicit guidance on when to prefer this tool over similar siblings (e.g., athena_collective_evaluate, athena_collective_plan) or when not to use it. The usage context is implied but not articulated with exclusions or alternatives, so it garners a 3.

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