Server Quality Checklist

Tool Scores

• search_logsB
  3.2/5.0
  Behavior2/5

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

  No annotations provided. Description reveals it returns matching entries up to a limit, but omits behavioral details like ordering, performance characteristics, or side effects.

  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, front-loaded with purpose, no wasted words.

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

  Completeness2/5

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

  With 6 parameters and no schema descriptions, the description is too brief. It lacks details on return format (despite output schema), ordering, and edge cases, making it incomplete given the tool's complexity and sibling context.

  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 description partially compensates for 0% schema coverage by referencing pattern, log level, and time range filters. However, it omits file_path (required) and max_results, leaving some parameters unexplained.

  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?

  Clearly states it searches log entries by regex, log level, and time range (verb+resource+scope). However, it does not explicitly differentiate from sibling tools like analyze_errors or classify_lines.

  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?

  Mentions combining filters and a max_results limit, but lacks explicit when-to-use guidance compared to alternatives and no prerequisites or exclusions.

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

• analyze_errorsB
  3.4/5.0
  Behavior3/5

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

  With no annotations, the description bears full responsibility for behavioral disclosure. It covers core behaviors (deduplication, frequency counting, stack trace extraction, grouping) but omits side effects, permission needs, or rate limits. The disclosed behaviors are helpful but not exhaustive.

  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 extremely concise: two sentences with no filler. The first sentence lists primary actions, and the second adds a key behavioral detail. Every word earns its place.

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

  Completeness3/5

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

  Given the output schema exists and the tool has 3 parameters, the description provides a solid high-level overview but lacks details about input file format, error pattern expectations, or limitations. It is adequate but not fully comprehensive.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description must compensate. It indirectly explains include_stack_traces by mentioning stack trace extraction, but file_path and max_unique_errors receive no explanation beyond their names. This leaves a significant gap for the latter two 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 purpose: analyze error entries by deduplicating via fingerprint, counting frequencies, and extracting stack traces. It also highlights the non-obvious grouping of similar messages, which distinguishes it from sibling tools.

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

  Usage Guidelines2/5

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

  The description does not provide guidance on when to use this tool versus alternatives like log_stats or classify_lines. No when-not scenarios are mentioned, leaving the agent to infer usage without explicit context.

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

• get_log_segmentA
  3.7/5.0
  Behavior3/5

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

  With no annotations, the description should disclose more behavioral traits. It mentions extraction methods but does not specify read-only nature, required permissions, or behavior when both range types are provided.

  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 with two well-structured sentences, each adding value and leading with the most important information.

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

  Completeness2/5

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

  Given 6 parameters, no annotations, and an output schema, the description is incomplete. It does not clarify parameter interactions, constraints (e.g., file size, time format), or cross-tool guidance with siblings.

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

  Parameters2/5

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

  Schema description coverage is 0%, so description must compensate. It mentions line/time ranges and max_lines but fails to specify time string format, exclusivity of ranges, or behavior when both ranges are given, leaving ambiguity.

  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 'Extract a segment of a log file' with a specific verb and resource, and the two extraction methods (line range, time range) are distinct from sibling tools like search_logs or analyze_errors.

  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?

  Provides clear guidance on when to use line ranges ('precise extraction around a known error line') versus time ranges ('all entries within a time window'), but does not address when to avoid this tool or compare to alternatives.

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

• compare_logsA
  3.8/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries full burden. It clearly discloses key behaviors: normalization of variable parts, comparison logic, and the types of results (unique, shared, frequency outliers). However, it does not mention potential side effects (none expected), file format assumptions, or performance considerations, which would improve 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 concise, with four sentences that are front-loaded with the main purpose. Every sentence adds value: purpose, normalization, outputs, and additional features. No unnecessary words or redundancy.

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

  Completeness3/5

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

  Given no annotations and an output schema (implied), the description covers the main functionality but lacks context about parameters and prerequisites. It does not mention that file paths must be valid or the meaning of thresholds. While the output schema likely explains return values, the description leaves gaps for parameter understanding.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description must add meaning to parameters. However, it does not explain any of the four parameters (file_paths, max_unique_per_file, max_shared_patterns, frequency_ratio_threshold). The description focuses on behavior, leaving parameter semantics to be inferred from names and defaults. This is insufficient.

  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: comparing multiple log files and finding entries unique to each file. It explains normalization of variable parts and the types of output (unique patterns, shared patterns, frequency outliers). This distinguishes it from sibling tools like analyze_errors or search_logs, which focus on different aspects.

  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 this tool (when you want to focus on differences across log files), but it does not explicitly state when not to use it or suggest alternatives. For example, it doesn't mention that for simple searching, search_logs might be better. The guidance is implicit rather than explicit.

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

• log_statsA
  3.9/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden for behavioral disclosure. It explains the outputs but lacks details on side effects (e.g., file modification), performance implications, required permissions, or whether it is read-only. For a tool that processes a file, more transparency is needed.

  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 two sentences long, with the first sentence front-loading the core purpose and outputs, and the second adding usage context. Every sentence is necessary and no repetition.

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

  Completeness3/5

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

  The tool has an output schema but the description does not mention return format; it lists outputs informally. It lacks details on file format expectations, size constraints, or behavior for missing files. Given the sibling context and parameter count, it is minimally adequate but has gaps.

  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 description coverage is 0%, yet the description partially compensates by linking parameters to outputs: 'volume histogram over time' implies bucket_size controls time bins, and 'top repeated message patterns' relates to top_patterns. However, it does not explain file_path or bucket_size values thoroughly.

  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 explicitly states what the tool does: 'Compute log statistics: volume histogram over time, level breakdown, and top repeated message patterns.' This clearly identifies the verb (compute) and resource (log statistics), with specific outputs that distinguish it from siblings like analyze_errors or search_logs.

  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 a clear usage context: 'Useful for spotting traffic spikes, error bursts, or noisy log sources.' While it does not explicitly list when not to use or alternatives, the provided scenarios guide appropriate invocation.

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

• classify_linesA
  4/5.0
  Behavior4/5

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

  With no annotations, the description fully shoulders the burden. It details the ML model (logistic regression), training data (17 datasets, 345M lines), and classification criteria. It also explains threshold behavior and output formats, giving a clear picture of behavior.

  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 a clear first sentence followed by a detailed Args section. Every sentence adds value, though the Args list could be more concise. Overall, it is appropriately sized for the complexity.

  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 five parameters, no annotations, and an output schema (though not shown), the description covers the tool's purpose, model, input, and output formats. It is sufficiently complete for an AI 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?

  Schema coverage is 0%, but the description explains all five parameters: file_path is mandatory, threshold effect is described, max_lines and max_look_lines are clarified, and output two options are detailed. This adds significant meaning beyond the raw 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 verb 'classify' and the resource 'log lines', specifying the classification outcome (LOOK vs SKIP). It distinguishes itself from sibling tools like analyze_errors and search_logs by focusing on ML-based binary classification.

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

  Usage Guidelines2/5

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

  The description lacks explicit guidance on when to use this tool versus alternatives. No comparison with siblings like analyze_errors or search_logs is provided, and there are no conditions or prerequisites mentioned.

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

• log_overviewA
  4/5.0
  Behavior4/5

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

  With no annotations, the description carries full burden. It discloses the outputs (size, line count, etc.) and implies read-only behavior via 'scan'. However, it does not state side effects or permissions explicitly, but for a read-like tool this is adequate.

  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 with no filler. Front-loaded with the core functionality, earning every word.

  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 tool's simplicity, the description is mostly complete. With an output schema present (context signal), the lack of return value detail is acceptable. Covers the basics for an overview tool.

  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 has 0% description coverage. The description mentions 'head/tail samples' hinting at sample_lines, but does not explicitly explain file_path or sample_lines. It provides some context but lacks full parameter meaning beyond the schema.

  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 clearly states it provides a quick scan with metrics like size, line count, time range, level distribution, and samples. It positions itself as a first step, but does not explicitly differentiate from siblings like analyze_errors or search_logs.

  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?

  Explicitly says 'Use this as the first step when investigating a log file', providing clear context for when to invoke it. No mention of when not to use or alternatives, but the guidance is specific and actionable.

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