Audit a YouTube script before recording

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

Annotations are minimal (readOnlyHint false, openWorldHint true, destructiveHint false), and the description adds crucial behavioral context: the result is 'released by email, so ask the user for an address rather than guessing one.' It also clearly scopes the analysis as a 'text-only check of an unrecorded script' that 'does not measure or predict published YouTube retention' and lists factors it cannot account for. No annotation contradiction.

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 long but front-loaded with the action and outputs, and every sentence contributes either selection guidance, an exclusion, or a limitation. Minor redundancy exists in restating 'text-only check' and 'maps relative attention risk,' but overall it is efficient for a tool with this complexity.

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?

The description covers purpose, selection criteria, outputs, side effects (email), and limitations in detail, compensating for the absence of an output schema. Given the tool's complexity (6 params, no output schema), nothing needed to invoke it correctly 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 every parameter's meaning, constraints, and required behavior. The description reinforces the email requirement and verbatim script_text handling, but these are also covered in the schema, so the description adds only marginal semantic value beyond the structured fields.

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 and resource: 'Run Prepublish's full audit on a YouTube script the user has already written.' It enumerates concrete outputs (hook, structure and pacing scores, attention-risk map, rewrites) and distinguishes itself by excluding script generation, published-video review, and grammar checking, which differentiates it from siblings like audit_hook and policy_preflight.

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?

Explicitly states when to choose it: 'when the user has a finished or near-finished draft and wants to know what is weak before they record.' It also gives clear when-not-to-use guidance: 'Do not use it to generate a script, to review a published video, or to check grammar.' This is direct selection context even without naming sibling tools.

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