lint_markdown

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

Excellent disclosure beyond annotations: details return structure (JSON array with line, column, severity, rule name, message, fixable flag) and enumerates specific lint rules checked (heading spaces, trailing whitespace, etc.). Matches readOnlyHint/destructiveHint annotations with 'report issues' framing.

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 sentences, zero waste. First sentence establishes purpose and return format; second enumerates specific checks. Perfectly front-loaded.

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?

No output schema exists, but description comprehensively documents return structure (array of issue objects with specific fields) and behavior. Combined with rich annotations (readOnly, idempotent), description provides complete context for invocation.

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 coverage is 100% ('markdown' parameter fully described), meeting baseline. Description adds no additional parameter semantics, but schema carries full burden adequately.

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?

Clear specific verb ('Lint') + resource ('Markdown') plus scope ('report issues'). Distinguished from conversion siblings (convert_to_*) and extraction siblings (extract_*) by focusing on validation/reporting.

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?

Provides implied usage through 'report issues' language, indicating read-only analysis. However, lacks explicit when-to-use guidance vs. close sibling 'repair_markdown' (which presumably fixes issues) or when to choose this over 'analyze_document'.

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