validate_variable_map

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

With no annotations, the description carries the full burden. It hints that conflicting observations are detected, but does not say whether the tool mutates the map, whether it throws on invalid input or returns a list of issues, or what the caller should expect back — and there is no output schema to compensate.

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 validated aspects are listed compactly. It is efficient, though its brevity is also the source of the missing detail noted elsewhere.

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?

For a validation tool taking a complex nested array with no annotations and no output schema, the definition should explain the result shape (pass/fail vs. issue list) and the meaning of the required fields. Neither is present, leaving an agent unable to predict outcomes.

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% on a single deeply nested parameter with ten documented-by-name-only fields. The description only gestures at names, offsets, widths, and conflicts, leaving key, kind, storage, type, confidence, evidence, and suggestions entirely unexplained, so it does not compensate for the coverage 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?

States a specific verb ('validate') and resource ('variable map'), and enumerates the aspects checked: names, offsets, widths, and conflicting observations. It is clearly distinct from infer_variables and suggest_variable_names, though it never names a sibling explicitly.

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 'before an ABI translation is reviewed' implies a workflow position after inference and before port validation, which is useful implied guidance. However, it never explicitly says when to use this versus infer_variables, suggest_variable_names, or port_validate_translation, and gives no when-not conditions.

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