suggest_titlesGenerate 5 compelling, SEO-friendly article title options from your existing article content. Use generate_title_seo instead if you want to target specific keywords or have not written content yet.
| Name | Required | Description | Default |
|---|---|---|---|
| context | Yes | Your article content in plain text or markdown |
Changes observed during successful MCP inspections.
Input schema / properties / context / descriptionPrevious value: -"The article text to draw titles from, plain or Markdown, 20-8000 characters. More of the real draft yields better-fitting titles than a summary."New value: +"Your article content in plain text or markdown"Input schema / properties / context / descriptionPrevious value: -"Your article content in plain text or markdown"New value: +"The article text to draw titles from, plain or Markdown, 20-8000 characters. More of the real draft yields better-fitting titles than a summary."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, non-destructive, open-world), and the description adds real behavioral context: the tool requires pre-existing content and always returns 5 options. It does not discuss variability/non-determinism of generation (annotations flag idempotentHint=false) or output format, so it falls short of full disclosure.
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 filler, with the core capability front-loaded and the routing rule second. Every clause carries information.
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 single-parameter read-only tool with full annotation coverage and no output schema, the description tells the agent what it produces (5 titles), what input it needs, and when to prefer a sibling. Only the shape of the returned value is left unspecified.
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% and the single 'context' parameter is fully documented there, so baseline 3 applies. The description's phrase 'from your existing article content' implicitly maps to that parameter but adds no format or length guidance beyond the schema's minLength/maxLength constraints.
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 (generate), resource (article title options), quantity (5), and qualifier (SEO-friendly from existing content). It also names the sibling it is not, so an agent can distinguish it from generate_title_seo without opening either schema.
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 second sentence gives an explicit when-to-use-the-alternative condition: use generate_title_seo when targeting specific keywords or when no content exists yet. This is a direct prerequisite and routing rule, not just implied context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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