Server Quality Checklist

Tool Scores

• stata_doB
  3.2/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden. It mentions the tool executes a do-file and optionally reads log on error, but fails to disclose side effects (e.g., file system changes), required permissions, or behavior on failure. This leaves significant gaps for a mutation-like tool.

  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 three sentences and concise, front-loading the main action. However, it could be more structured by linking parameters to their roles, but it is not overly verbose.

  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 and an output schema, the description is incomplete. It does not explain most parameters (e.g., timeout, log options) beyond a brief mention of error-triggered log reading. This forces the agent to guess parameter semantics, reducing usability.

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

  Parameters1/5

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

  Schema description coverage is 0%, yet the description adds no detail for parameters beyond mentioning 'dofile_path'. Parameters like 'timeout', 'enable_smcl', 'log_file_name', 'is_replace_log', and 'read_log_when_error' are completely unexplained, making it hard for an agent to use them correctly.

  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 executes a Stata do-file and returns the execution log, with a specific verb ('Execute') and resource ('Stata do-file'). It distinguishes itself from siblings like 'read_log' and 'get_data_info' by focusing on running do-files for statistical analysis.

  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 explicitly tells when to use the tool: 'Use when you need to run Stata commands, perform regression or statistical analysis, or execute a do-file.' It does not mention when not to use or alternatives, but the context is clear and helpful for an agent.

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

• helpA
  3.6/5.0
  Behavior3/5

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

  No annotations are provided, so the description must cover behavioral aspects. It states the tool 'retrieves documentation,' which implies a read-only operation, but it does not disclose the format of the output (e.g., text, pager) or any potential side effects. The description is adequate but minimal.

  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, front-loads the purpose, and contains no redundant information. 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?

  The tool is simple with an output schema, but the description lacks parameter documentation, which is essential for correct usage. It does not mention whether the command requires internet or works offline. It is minimally complete for a help tool but leaves gaps.

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

  Parameters1/5

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

  Schema coverage is 0%, meaning the description adds no explanation for the two parameters ('cmd' and 'replace'). The agent receives no guidance on what 'cmd' expects (e.g., a string of the command name) or the effect of 'replace' (e.g., overwriting existing help file). This is a critical gap.

  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 ('Retrieve') and the resource ('documentation and usage information for a Stata command'). This distinguishes it well from siblings like 'stata_do' (execute code) and 'get_data_info' (data information).

  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 explicit context for when to use the tool: 'Use when you need to understand a command's syntax, options, or troubleshoot errors before running it.' It does not specify when not to use it or mention alternatives, but the positive guidance is strong and clear.

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

• read_logA
  3.6/5.0
  Behavior3/5

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

  No annotations provided, so description carries full burden. It does not explicitly state that the operation is read-only or describe any side effects, authentication needs, or constraints. However, the read nature is implied.

  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?

  Three sentences, all informative, no wasted words. Front-loads purpose and adds details about formats and the lines parameter efficiently.

  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 4 parameters, no annotations, and presence of output schema, the description covers the basics but leaves gaps in parameter meaning (encoding, file_path) and does not fully compensate for missing schema descriptions.

  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 coverage is 0%, so description must explain parameters. It describes output_format enum values and lines parameter but does not clarify encoding or file_path. The lines behavior (positive/negative for first/last) is ambiguous.

  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 reads Stata log files (.log or .smcl) and returns content, with verb 'Read' and resource 'log file'. It distinguishes from siblings (get_data_info, help, stata_do) by specifying the file type and output formats.

  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?

  Provides basic guidance on output formats and lines parameter, but does not explicitly state when to use the tool vs. alternatives, nor when not to use it. Usage context is implied but not formalized.

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

• get_data_infoA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description must convey behavioral transparency. It implies a non-destructive read operation via 'Get' and 'preview', but does not explicitly state that no file modifications occur or address error/permission behavior. It adds some context with supported formats and output shape, but safety traits are left to inference.

  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 that are front-loaded and efficient. The first sentence states the core function and return outputs; the second gives the usage trigger. No filler or redundant content.

  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 data-info tool with an output schema, the description covers the essential purpose, supported formats, return summary, and usage context. It misses the encoding parameter and does not specify whether the tool is read-only, but overall it is sufficiently complete for an agent to invoke it correctly in most scenarios.

  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 0%, so the description must compensate. It explains 'optional head rows' (head) and 'filtered by requested variables' (vars_list), and data_path is implied by 'data file'. However, the encoding parameter is not mentioned, leaving 1 of 4 parameters undocumented. The description partially mitigates the schema gap but not completely.

  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: 'Get descriptive statistics and a data preview for a supported data file' with explicit file format list. It specifies the return content (overview, variable details, optional head rows) and distinguishes itself from unrelated siblings like read_log and stata_do.

  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 gives a clear use case: 'Use when you need to understand a dataset or have no prior knowledge of the data.' It does not explicitly mention when not to use or alternatives, but the context implies it's the primary tool for data exploration.

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