Server Quality Checklist

Tool Scores

• diagnose_logA
  3.9/5.0
  Behavior4/5

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

  Annotations already mark the tool as readOnlyHint=true and openWorldHint=false. The description adds meaningful behavioral context beyond that: it reduces the log to one error signature, chooses the most specific failure line rather than the last one, and returns documentation pages. This is useful, non-contradictory transparency.

  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 compact and well-structured: a front-loaded purpose statement, a short behavioral clarification, and a one-line parameter specification. Every sentence adds value, and the most important constraint (300-line limit) is stated explicitly.

  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?

  For a single-parameter tool with an output schema and read-only annotations, the description covers the key operational details an agent needs: input format, log truncation, and the error-reduction behavior. It does not specify what happens when no error signature is found, but the existing output schema reduces that burden.

  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 0%, so the description must carry the parameter meaning. It does: 'log: The raw log text. Only the last 300 lines are read.' This clarifies both the content and a critical truncation behavior for the single parameter.

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

  Purpose4/5

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

  The description states a specific verb and resource: 'Extract the error from a failing build or runtime log and fetch the docs for it.' It clearly conveys a diagnostic workflow distinct from a generic docs search, though it does not explicitly name sibling tools or state what makes it different from search_docs.

  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 when to use the tool—when you have a failing build or runtime log—and includes the input constraint that only the last 300 lines are read. However, it does not explicitly contrast with alternatives like search_docs or read_page, nor does it state when those should be preferred.

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

• platform_docsA
  4.5/5.0
  Behavior4/5

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

  With readOnlyHint=true and openWorldHint=false already covering the read-only and closed-world safety profile, the description adds the aggregation behavior: it collects multiple pages for one platform and includes the full liara.json reference. No side effects or failure modes are described, but none are required given 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.

  Conciseness5/5

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

  The description is about 60 words: a one-sentence purpose, a one-sentence output description, and formatted Args. No sentence is wasted, and the key action is front-loaded.

  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?

  The tool has only two parameters, an output schema exists (so return values need not be described), and annotations cover the safety model. The description covers purpose, output contents, and both parameters, leaving no essential invocation detail missing.

  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?

  The schema has 0% coverage, and the 'Args' section compensates by explaining that 'platform' is the target and 'needs' is an optional list of extra lookups, with examples ('disk', 'cron', 'websocket') and a maximum of 10 items. This is enough for an agent to construct valid calls.

  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 opening sentence names a specific verb ('collect'), a specific resource ('deployment documentation for one platform'), and the intended end-goal ('ready to write a liara.json'). It also enumerates the return contents (quick start, deployment, env-var pages, liara.json reference), which separates it from the generic search_docs/read_page siblings.

  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 phrase 'ready to write a liara.json' gives an explicit scenario for choosing this tool. It does not name sibling alternatives or exclusion conditions, but the context is unambiguous enough to route selection.

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

• read_pageA
  4.8/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true and openWorldHint=false, so the read-only nature is covered. The description adds meaningful behavioral context: the tool cannot fetch arbitrary URLs and reads only already-indexed pages, which is valuable beyond 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.

  Conciseness5/5

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

  Every sentence earns its place: the purpose is front-loaded, the critical limitation is stated next, and the parameter explanation is brief and direct. No filler or redundancy.

  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?

  For a single-parameter read tool with annotations and an output schema, the description is complete. It covers the prerequisite (previous search), the constraint (no arbitrary URLs), and the exact parameter expected. Nothing needed to call it correctly is missing.

  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?

  Schema description coverage is 0%, so the description must carry the burden for parameter meaning. It does so clearly by stating that 'url' must be a canonical docs.liara.ir URL taken from a search result, which is essential information the schema alone does not provide.

  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 states a specific action ('Read one whole documentation page') and a specific resource ('the local corpus'), which clearly distinguishes it from the sibling tools. The addition that only pages returned by a prior search can be fetched makes its scope unambiguous.

  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 gives explicit when-to-use guidance: the URL must come from a previous search result, and no other URL can be fetched. It also explains the underlying reason (no HTTP client, only indexed content), leaving no ambiguity about when this tool applies.

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

• search_docsA
  4.8/5.0
  Behavior4/5

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

  The annotations already declare readOnlyHint=true, so no contradiction. The description adds useful behavioral detail by specifying that the result includes numbered snippets with source URLs, and the parameter descriptions disclose truncation and clamping behavior, going beyond the minimal annotation info.

  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 compact and well-structured: a purpose sentence, a usage directive, a language tip, and then concise parameter explanations. No redundant or filler content; every sentence earns its place.

  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 (2 params, output schema present), the description covers all necessary aspects: what it does, how to use it, parameter semantics, and output format. The presence of an output schema means detailed return structure is not needed in the description, so completeness is high.

  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?

  The schema has no descriptions for the parameters (0% coverage), but the description fully compensates by explaining query as 'What to search for' with a 300-character truncation limit, and k as 'How many snippets to return' with a 1–8 range and clamping. This adds complete meaning to both 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 tool's function: searching the Li documentation and returning numbered snippets with source URLs. It also explicitly says to use it for every factual claim about Liara, which contrasts with the sibling tools (read_page, platform_docs, diagnose_log) that serve different purposes.

  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 provides explicit when-to-use guidance: 'Use this for every factual claim about Liara.' It also gives concrete query formulation instructions (use the user's own words plus the product name, both Persian and English work), making the usage context unmistakable.

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