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

With no annotations provided, the description must carry the behavioral disclosure burden. 'Track calibration' hints at possible state tracking or updates, but it is unclear whether this tool mutates calibration state, only evaluates, or has side effects. No safety or persistence behavior is disclosed.

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?

A single, front-loaded sentence with no filler. The core purpose and classification categories are stated immediately, and the wording is compact while conveying meaningful detail.

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?

Despite an output schema, the definition is incomplete for correct invocation: parameter semantics are missing, behavioral side effects are ambiguous, and usage context versus sibling tools is absent. For a metacognitive tool with zero annotations and zero schema descriptions, the description does too little to make the tool safely and correctly callable.

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%, so the description must compensate. It gives conceptual context for task classification but never explains the meaning or expected shape of 'task_structure' or the role of 'actual_outcome' in calibration. The agent is left to guess how to populate either parameter.

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 uses a specific verb ('classify') with a clear resource ('task') and names the exact output categories (KNOWN, KNOWN_UNKNOWN, UNKNOWN_UNKNOWN). It implies a distinct epistemic-assessment role among the cognitive tools, though it does not explicitly contrast itself with siblings like identify_task or parse_task.

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 phrase 'Epistemic boundary awareness' implies use when the agent needs to determine whether a task is known, known-unknown, or out-of-distribution. However, there is no explicit guidance on when to prefer this tool over related siblings, nor any stated exclusions or prerequisites.

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