Server Quality Checklist

Tool Scores

• lint_producthunt_postA
  4.1/5.0
  Behavior4/5

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

  The description discloses that prohibited terms are enforced on the entire post without exceptions, and explains the real-world consequence (Product Hunt removes the post), adding behavioral context beyond the read-only/idempotent annotations. It does not contradict the annotations.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is compact and front-loaded with the primary purpose, followed by differentiation, parameter list, and return value. The Args section is somewhat redundant with the schema, but it is the only minor waste.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The description covers purpose, usage, differences from a sibling, parameters, and return behavior ('PASS'/'FAIL' with structuredContent). Combined with annotations and an existing output schema, it provides sufficient context for the agent to decide and invoke correctly. It could mention edge cases like invalid config, but that is not critical for basic usage.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  All 4 parameters have schema descriptions (100% coverage), so the input schema already provides clear semantics. The description's Args section briefly reiterates the parameters but adds no new meaning beyond the schema, e.g., 'imageCount' is already described as checking gallery.min_images in the schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool validates a Product Hunt tagline and description against hard limits in PRODUCTHUNT.md, using a specific verb ('Valida'). It explicitly contrasts with lint_web_content, distinguishing the tool's scope (whole post vs short surface).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides an explicit usage guideline by distinguishing this tool from lint_web_content: it explains that prohibited terms are blocked across the entire post, not just a short surface, which tells the agent when this tool is appropriate over the sibling. However, it does not explicitly address alternatives like lint_linkedin_content, so it is a bit incomplete.

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

• lint_web_contentA
  4.5/5.0
  Behavior5/5

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

  Even with annotations declaring readOnlyHint, idempotentHint, and destructiveHint, the description adds deep behavioral detail: hard vs. soft gates, 'términos prohibidos' handling in body vs. title/meta, density never requiring presence, forbidden_structure, JSON-LD validation, and error handling as violations. This goes far beyond the structured annotations.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is long but every sentence carries substantive information. It is front-loaded with the core purpose, then organized into validation checks, arguments, return value, and error behavior. No fluff or redundancy undermines its usefulness.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity, the description is remarkably complete: it covers return format ('PASS'/'FAIL' plus detailed per-page output), structuredContent, error conditions, and edge cases like false-positive prevention for forbidden terms in body. The existence of an output schema further reduces the burden, but the description is still thorough.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The input schema already provides 100% coverage with descriptions for both config and pages. The description mostly restates this info (e.g., 'config (string): el bloque YAML de frontmatter', 'pages (array): páginas a validar') without adding significant new semantic detail beyond the schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states a specific action: 'Valida una o más páginas HTML contra los techos/pisos duros declarados en un SEO.md'. It names the resource (HTML pages, SEO.md) and distinguishes from siblings like lint_producthunt_post and lint_linkedin_content by targeting web content.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides clear context: it is a read-only validation tool for HTML pages against SEO.md rules, and explicitly says 'No escribe contenido — solo verifica lo que ya se escribió'. However, it does not explicitly name alternative tools or state when not to use it versus the sibling linters.

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

• export_json_ldA
  4.6/5.0
  Behavior5/5

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

  The description adds behavioral context beyond annotations: it is 'templating puro sobre el YAML, sin LLM', failure behavior is specified ('el tool falla con un mensaje claro'), and required input fields are listed. Annotations already declare readOnlyHint and idempotentHint, and the description does not contradict them.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is well-structured with args and returns, but includes slightly verbose phrasing like 'cero ambigüedad posible (SEO.md, regla 6)'. It remains efficient and each sentence serves a purpose, earning a 4 rather than lower.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the output schema exists and annotations are present, the description is complete: it covers prerequisites, parameter semantics, behavior, and output. No important gaps remain.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, so baseline is 3. The description adds extra semantics by explaining that config must contain a `schema:` block with specific fields (default_type, name, description) and that url is optional to add a "url" field. This enriches understanding beyond the schema descriptions.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose: 'Genera el bloque JSON-LD (<script type="application/ld+json">) a partir del bloque `schema:` de un SEO.md'. This uses a specific verb (genera) and resource (JSON-LD block from SEO.md), and it is clearly differentiated from sibling lint tools.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides clear context for when to use the tool (to generate JSON-LD from SEO.md), including required fields and failure conditions. However, it does not explicitly mention alternatives or when not to use it, but the context is strong enough to avoid confusion with the lint siblings.

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

• lint_linkedin_contentA
  5/5.0
  Behavior5/5

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

  The description discloses that article content is structured ('El contenido del artículo es estructurado...') and warns against regex parsing, plus specifies the return format ('PASS'/'FAIL' with structuredContent). Annotations already declare read-only and idempotent, so this adds valuable behavioral context without contradiction.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Every sentence earns its place: validation scope, structured-content expectation, sibling differentiation, and parameter recap are all tightly packed. The description is well-organized and appropriately sized for the tool's complexity.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the rich schema and annotations, the description covers all necessary aspects: purpose, usage boundaries, behavioral quirks, return format, and parameter relationships. No significant information is missing for an agent to select and invoke the tool correctly.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters5/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Beyond the near-complete schema, the description clarifies that the two formats share almost no real restrictions, requires at least one of feedCopy/newsletter, and explains that counting sections is reading the array length. These operational details greatly help correct invocation.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description opens with 'Valida un copy de feed y/o un artículo de newsletter de LinkedIn contra los techos duros de un LINKEDIN.md', using a specific verb and resource, and explicitly distinguishes itself from lint_web_content via the forbidden_structure difference. This clearly identifies the tool's scope and sets it apart from siblings.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description explicitly contrasts with lint_web_content ('a diferencia de lint_web_content'), indicating when to use this tool for LinkedIn-specific structural checks. It also gives clear parameter guidance: 'mandá al menos uno de los dos, podés mandar ambos', which is not captured in the schema.

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