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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds the meaningful fact that it will 'auto-repair' as well as validate, but never explains what repair means in practice (type coercion? dropping unknown keys?), how failures are surfaced, or what comes back. The endpoint string is operational trivia rather than behavior.

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?

Two compact sentences with the core action front-loaded and no filler prose. The trailing '(Endpoint: POST /v1/tool-call-validator)' is largely wasted space for an agent choosing a tool, keeping it out of the top tier.

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?

This is a nested-object tool with no output schema, yet the description never indicates the shape of the result — whether it returns a repaired tool_call, a validity boolean, or a list of errors. For a read-only validator whose whole value is its verdict, that return-side gap matters, and the undefined meaning of 'repair' compounds it.

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 100%, so the schema documents all three parameters and the baseline is 3. The description goes slightly beyond by stating that validation is performed 'against your JSON Schema', which hints at the relationship between the supplied tool definitions and the call being checked, though it does not map that phrase explicitly onto the 'tools' 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 names a specific verb pair ('Validate and auto-repair') and a specific resource ('broken LLM tool-call arguments against your JSON Schema'), so an agent can tell this acts on tool calls rather than arbitrary JSON. It does not explicitly contrast itself with nearby siblings such as tinplate_json_heal or tinplate_llm_output_guard, so the differentiation is implicit rather than stated.

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?

There is no when-to-use or when-not-to-use guidance, and no named alternative for the closely related repair/heal tools in the sibling list. The agent must infer from the title alone that this is the right choice when a tool call's arguments are malformed, and nothing says what to do when the JSON is valid already.

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