Validate a PDF template DSL script for structure, tag/style correctness, and accessibility issues. Runs catalog validation plus alt-text checks. Cheap — no rendering. Mirrors POST /api/v1/preview/validate.
| Name | Required | Description | Default |
|---|---|---|---|
| dsl | Yes | The builder DSL script to validate. Must define a template (see skills/pdf-template-author.md). | |
| data | No | Optional binding data. Falls back to the script's sampleData when omitted. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It usefully discloses that the tool runs catalog validation plus alt-text checks and that it performs no rendering, which is a meaningful behavioral trait. It does not explicitly state side effects or return behavior, but validation implies a non-mutating, read-only operation.
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 four tight sentences with no filler. The main purpose is front-loaded, and each sentence adds value: validation scope, checks performed, cost/rendering behavior, and API mirror. This is an efficient, well-structured description.
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 the tool's purpose, validation scope, performance characteristics, and API relation. With complete parameter schema and one required parameter, an agent can likely invoke it correctly. However, the description does not state what the validation result looks like (e.g., issues list, pass/fail), which is a minor gap given there is no output schema.
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%, with clear descriptions for dsl and data. The tool description adds general context about validation categories but does not add parameter-specific meaning beyond the schema's own descriptions. Baseline 3 is appropriate because the schema already documents the parameters.
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: 'Validate a PDF template DSL script.' It names exact validation dimensions (structure, tag/style correctness, accessibility) and distinguishes itself from preview/rendering tools with 'Cheap — no rendering.' This clearly differentiates it from sibling tools like render_dsl_preview and validate_markdown.
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 description gives clear usage context by stating 'Cheap — no rendering,' which implies this is the lightweight validation path versus render_dsl_preview. It also signals API parity with 'Mirrors POST /api/v1/preview/validate.' However, it does not explicitly mention when to prefer this over validate_markdown or name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.