Server Quality Checklist

Tool Scores

• clean_contentA
  3.8/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden of behavioral disclosure. It explains the transformation (removing noise, keeping text) and return type (readable plain text). However, it does not mention edge cases like malformed HTML, performance, idempotency, or whether the input is mutated.

  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 three sentences, front-loaded with the action 'Clean raw HTML'. Every sentence serves a purpose: specifying what is removed, what is kept, and the return type. No fluff.

  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?

  Given no output schema, the description adequately explains the return value (plain text with structure). It covers both parameters and the core behavior. Missing details on error handling or potential performance implications, but overall sufficient for the tool's simplicity.

  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?

  Schema coverage is 100%, so baseline is 3. The description does not add new meaning beyond the schema: 'url' is for relative link resolution (as schema notes), 'html' is the input. No parameter-specific elaboration in the description.

  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: 'Clean raw HTML' by removing specific elements (scripts, styles, navigation, etc.) and keeping meaningful content (headings, paragraphs, tables, lists). It distinguishes itself from siblings like scrape_website or chunk_content by focusing on cleaning/transforming HTML to plain text.

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

  Usage Guidelines3/5

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

  The description implies use after scraping HTML, but it does not explicitly state when to use versus alternatives like chunk_content (which splits text) or when not to use (e.g., if HTML is already clean). No exclusions or specific context cues are provided.

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

• scrape_websiteA
  4/5.0
  Behavior4/5

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

  The description discloses auto-detection of static vs dynamic pages and the return payload. With no annotations, it covers key behaviors but omits error handling, rate limits, or consent requirements.

  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?

  Two sentences with zero redundancy. Front-loaded with purpose, then technical details. Every sentence adds value.

  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?

  Given a single required parameter and no output schema, the description adequately explains functionality and outputs. Could mention pagination or size limits, but overall sufficient.

  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?

  Schema coverage is 100% and the description adds no extra meaning to the URL parameter beyond what the schema provides. Baseline score applies.

  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 'Scrape a single web page' and lists specific outputs (title, content, links, metadata). It distinguishes from sibling tools by focusing on a single page, not crawling or content processing.

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

  Usage Guidelines3/5

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

  The description implies single-page usage but does not explicitly tell when to use alternatives like crawl_website or scrape_full_site. No exclusion criteria are mentioned.

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

• crawl_websiteA
  4.1/5.0
  Behavior4/5

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

  With no annotations, description fully discloses crawl behavior: BFS algorithm, internal links only, respects robots.txt, avoids duplicates, limits depth and page count. Also states returned data (title, content, links). Lacks details on rate limiting or performance impact but is still thorough.

  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?

  Extremely concise: two sentences covering purpose, behavior, constraints, and output. No redundancy or filler. Information-dense and efficient.

  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 no output schema, the description adequately explains return values (title, content, links). Covers all input parameters, behavior, constraints, and output format. No missing critical information for a crawl tool with two params.

  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?

  Schema coverage is 100%, and both parameters are well-described in the schema. The description adds minimal extra context (e.g., 'link-hops' for max_depth) but does not enhance understanding beyond schema defaults and bounds.

  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?

  Description clearly states the tool's purpose: BFS-crawl an entire website from a root URL. It specifies algorithm, constraints (internal links, robots.txt, duplicate avoidance, depth/count limits), and output (title, content, links). This distinguishes it from sibling tools like 'scrape_website' (presumably single-page) and 'scrape_full_site'.

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

  Usage Guidelines3/5

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

  Usage is implied: use for full-site crawling. However, no explicit guidance on when to use this tool versus alternatives like 'scrape_website' or 'scrape_full_site'. No when-not-to-use or prerequisite info provided.

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

• scrape_full_siteA
  4.2/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the full behavioral burden. It details the pipeline steps (crawl, clean, optionally chunk) and the return structure (title, content, links, metadata, chunks). It also mentions handling both static and dynamic pages, adding valuable context. However, it does not address resource consumption, rate limits, or authentication.

  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?

  Two concise sentences: first describes the pipeline, second defines the return. No wasted words and front-loaded with the key action.

  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?

  Given the complexity of crawling and cleaning, the description covers the main outputs and mentions dynamic page handling. It lacks details on the cleaning process, max_depth behavior, or prerequisites like authentication, but remains largely complete for selection purposes.

  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?

  Schema description coverage is 100%, so the schema already documents each parameter. The description does not add additional meaning beyond what the schema provides, placing it at the baseline of 3.

  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 it's an end-to-end pipeline for crawling every internal page, cleaning HTML, and optionally chunking. It distinguishes from siblings like crawl_website, scrape_website, chunk_content, and clean_content by combining all steps.

  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 explains what the tool does and implies use cases for full-site scraping, but does not explicitly state when not to use it or list alternatives such as crawl_website or scrape_website for simpler tasks.

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

• chunk_contentA
  4.5/5.0
  Behavior4/5

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

  The description discloses key behavioral traits: overlapping chunks, deterministic IDs from URL and position. No annotations are provided, so the description carries the full burden. It does not mention edge cases or side effects, but for a text transformation tool, the behavior is sufficiently transparent.

  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 concise and front-loaded, with three sentences that each serve a purpose: stating the action, detailing the chunk characteristics, and suggesting use cases. No wasted words.

  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 simplicity, the description covers all necessary information: what it does, how it operates (overlap, chunk size, ID generation), and its intended use. No output schema exists, but the behavior is clear enough.

  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 the baseline is 3. The description adds value beyond the schema by explaining how parameters are used: overlapping mechanics, deterministic ID derivation from URL, and the general split strategy, which enriches the meaning of the parameters.

  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 action ('Split clean text into overlapping chunks'), specifies chunk size (~1000 characters) and overlap (200 characters), and distinguishes from sibling tools (cleaning, crawling, scraping) by focusing on the chunking process.

  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 mentions use cases ('preparing text for vector embedding or search indexing'), providing clear context. However, it does not explicitly state when not to use the tool or compare to alternatives, though the sibling tool names imply distinct purposes.

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