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

The description adds meaningful behavior beyond annotations: auth requirements and cost ('free-trial or X-Vibes-Key preferred; else x402 (~$0.02)'), side-effect profile ('none local; compute-only remote call'), idempotency, and a possible payment_required return. This supplements the readOnlyHint and idempotentHint annotations without contradicting them.

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 compact, front-loaded with the main purpose, and every line earns its place: trigger, exclusion, auth, side effects, and return behavior. It uses short labeled sentences instead of vague filler.

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 simple repair tool with two well-documented parameters and an output schema, the description covers the essential context: when to use it, when not to, auth/cost, idempotency, side effects, and return outcome including payment_required. No critical operating detail is missing.

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 already documents both 'text' and 'payment_signature' clearly. The description adds cost/auth context mentioning x402, but it does not materially improve parameter semantics beyond what the schema provides.

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 opens with a specific verb and resource: 'Repair malformed JSON from LLM output and return valid parsed JSON.' It also explicitly contrasts with web fetching/search tools, naming vc_web_search and vc_page_markdown, so an agent can distinguish it from siblings.

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?

It gives a clear trigger condition: 'Use when a model returned broken JSON (trailing commas, missing quotes, etc.).' It also provides a direct exclusion and alternatives: 'Do not use for web fetching or search — use vc_web_search / vc_page_markdown.'

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