Server Quality Checklist

Tool Scores

• fetch_gfsmab_dataB
  3.1/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a retrieval/read operation and mentions not to retry on failure, which is helpful. However, it doesn't address important aspects like rate limits, authentication requirements, data format details, error handling beyond the no-retry instruction, or whether the operation is idempotent.

  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 clear sections for Args and Returns. Each sentence serves a purpose: the first states the overall function, the Args section documents parameters, and the Returns section provides important behavioral guidance. There's minimal wasted text, though the parameter explanations could be slightly more detailed.

  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?

  For a 6-parameter data retrieval tool with no annotations and no output schema, the description provides adequate but incomplete context. It covers parameter semantics well and gives critical behavioral guidance about not retrying on failure. However, it lacks information about the return format (beyond 'Description of the queried data'), error types, data volume limits, or how results are structured.

  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?

  With 0% schema description coverage, the description provides essential semantic context for all 6 parameters. It explains what each parameter represents (e.g., 'Frequency', 'Country code', 'Unit code'), provides examples for 'freq' and 'unit', and clarifies that country codes can be combined with '+'. This significantly compensates for the lack of schema descriptions.

  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 the verb ('Retrieves') and resource ('compact format time series data from the GFSMAB database'), making the purpose specific and understandable. It distinguishes this tool from siblings by specifying the GFSMAB database source, but doesn't explicitly contrast with other data-fetching tools like fetch_bop_data or fetch_ifs_data.

  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?

  No guidance is provided on when to use this tool versus alternatives like fetch_bop_data or fetch_ifs_data. The description mentions the GFSMAB database but doesn't explain what type of data it contains or when it's preferred over other data sources. There's no mention of prerequisites or typical use cases.

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

• list_indicatorsB
  3.1/5.0
  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 of behavioral disclosure. It mentions reading from a local .json file, which hints at a read-only operation without external calls, but does not specify permissions, error handling, or data format details. This leaves gaps in understanding the tool's behavior for a mutation-free context.

  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 appropriately sized and front-loaded, with the core purpose stated first, followed by parameter and return details in a structured format. Every sentence adds value, though the 'Returns' section could be slightly more informative given the lack of output schema.

  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 tool's low complexity (1 parameter, no nested objects, no output schema) and no annotations, the description is minimally adequate. It covers the basic purpose and parameter semantics but lacks details on error cases, data structure, or integration with sibling tools, leaving room for improvement in completeness.

  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 description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'dataset_id' corresponds to dataset IDs like 'IFS', 'DOT', etc., and clarifies it's used to read from a specific .json file. This compensates well for the low schema coverage, though it doesn't detail all possible dataset values or file locations.

  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 the tool's purpose: 'Returns a list of indicators for the specified dataset' with the specific action 'read from the corresponding .json file in the local indicators directory.' It distinguishes from sibling tools like 'list_countries' by focusing on indicators rather than countries, though it doesn't explicitly differentiate from data-fetching siblings like 'fetch_ifs_data' beyond the resource type.

  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 provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'list_countries' for listing other resources or data-fetching tools like 'fetch_ifs_data' for retrieving actual data. Usage is implied by the purpose but lacks explicit context or exclusions.

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

• fetch_cdis_dataB
  3.2/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves data and warns against retrying on failure, which adds some context. However, it lacks details on permissions, rate limits, data freshness, or error handling specifics. The description doesn't contradict annotations (none exist), but it's insufficient for a mutation-like tool with 6 parameters.

  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 purpose statement, parameter list, and return instruction. It's front-loaded with the main function. However, the parameter explanations could be more concise, and the 'Returns' section includes operational advice that might be better placed elsewhere, slightly reducing efficiency.

  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 6 parameters, 0% schema coverage, no annotations, and no output schema, the description is moderately complete. It covers the basic purpose and parameters but lacks details on data format, error responses, or integration with siblings. For a data retrieval tool with multiple similar siblings, more contextual guidance would improve completeness.

  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 lists all 6 parameters with brief explanations (e.g., 'Frequency (e.g., "A" for annual)'), adding meaning beyond the schema's minimal titles. However, it doesn't provide examples for all parameters, validation rules, or format details (e.g., country code standards), leaving gaps in understanding.

  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 the tool 'retrieves compact format time series data from the CDIS database based on input parameters,' which specifies the verb (retrieves), resource (CDIS database data), and format (compact time series). It distinguishes from siblings like list_countries or list_indicators by focusing on data retrieval rather than metadata listing, though it doesn't explicitly differentiate from similar fetch_* tools like fetch_bop_data.

  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 provides no guidance on when to use this tool versus alternatives like other fetch_* tools (e.g., fetch_bop_data, fetch_cpis_data). It mentions 'Do not perform further analysis or retry if the query fails,' which is a behavioral instruction but not usage context. There is no mention of prerequisites, dependencies, or scenarios favoring this tool over siblings.

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

• list_countriesB
  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 full burden for behavioral disclosure. It mentions the data source ('.json file in the local areas directory') which adds useful context, but doesn't cover important aspects like whether this is a read-only operation, potential rate limits, error conditions, or what happens if the dataset_id doesn't exist.

  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 perfectly structured and concise. It begins with the core purpose, then provides clear Args and Returns sections. Every sentence earns its place, with no redundant information or wasted words.

  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?

  For a single-parameter read operation with no output schema, the description is adequate but has gaps. It explains what the tool does and the parameter meaning well, but lacks information about return format details, error handling, or how it relates to sibling tools. The absence of annotations means more behavioral context would be helpful.

  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 description provides excellent parameter semantics despite 0% schema description coverage. It explains that dataset_id represents 'Dataset ID, such as "IFS", "DOT", "BOP", etc.' and connects it to the sibling tool names, giving concrete examples that the schema lacks. This fully compensates for the schema coverage gap.

  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 the tool's purpose: 'Returns a list of available countries for the specified dataset'. It specifies the verb ('returns'), resource ('list of available countries'), and scope ('for the specified dataset'), though it doesn't explicitly differentiate from sibling tools like 'list_indicators'.

  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 provides no guidance on when to use this tool versus alternatives. It mentions reading from '.json file in the local areas directory', but doesn't specify prerequisites, when-not-to-use scenarios, or compare it to sibling tools like 'fetch_*' tools that might also involve country data.

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

• fetch_dot_dataB
  3.3/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves data (implying read-only) and explicitly warns not to retry on failure, which adds useful context about error handling. However, it lacks details on rate limits, authentication needs, data freshness, pagination, or what constitutes a 'failure' (e.g., invalid parameters vs. server errors). The description doesn't contradict annotations since none exist.

  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 and appropriately sized. It starts with a clear purpose statement, followed by an 'Args' section detailing parameters with helpful examples, and ends with return behavior. Every sentence adds value, though the return statement could be integrated more smoothly. No wasted 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 6 required parameters, 0% schema coverage, no annotations, and no output schema, the description does a decent job but has gaps. It explains parameter meanings well and gives behavioral hints (no retry on failure), but lacks context on sibling tools, error types, data format details, or usage scenarios. For a data retrieval tool with complex inputs, more guidance would improve completeness.

  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%, so the description must compensate. It provides clear semantics for all 6 parameters: freq (frequency with example 'A' for annual), country (country code with multi-code syntax using '+'), indicator (indicator code), counterpart (counterpart country code), and start/end (years). This adds significant value beyond the bare schema, though it could benefit from examples for indicator/counterpart codes or format details for start/end.

  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 the tool's purpose: 'Retrieves compact format time series data from the DOT database based on the input parameters.' It specifies the verb ('Retrieves'), resource ('time series data from the DOT database'), and format ('compact format'). However, it doesn't explicitly differentiate from sibling tools like fetch_bop_data or fetch_ifs_data, which likely retrieve different datasets from similar databases.

  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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools, explain what distinguishes DOT data from other datasets (e.g., BOP, CPI), or specify prerequisites like required permissions or database access. The only contextual hint is the return statement about not retrying on failure, but this doesn't help with tool selection.

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

• fetch_fsi_dataB
  3.3/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves data (implying read-only) and specifies 'Do not perform further analysis or retry if the query fails,' which adds important behavioral context about error handling. However, it doesn't mention rate limits, authentication requirements, data format details, or what constitutes a 'compact format.'

  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 clear sections (purpose, Args, Returns). Each sentence earns its place by providing essential information. The Args section is particularly efficient in explaining multiple parameters concisely. The only minor improvement would be integrating the purpose statement more seamlessly with the parameter explanations.

  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?

  For a 5-parameter tool with no annotations and no output schema, the description provides adequate but incomplete coverage. It explains parameters well and gives behavioral guidance about error handling, but doesn't describe the return format ('compact format' is vague) or provide examples of valid indicator/country codes. Given the complexity and lack of structured documentation, it should do more to compensate.

  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?

  With 0% schema description coverage, the description must compensate for the lack of parameter documentation. It provides clear explanations for all 5 parameters: frequency format examples, country code concatenation syntax, and start/end year formats. The only gap is that 'indicator' lacks examples of valid codes, but overall the description adds substantial value beyond the bare 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 the tool's purpose: 'Retrieves compact format time series data from the FSI database based on the input parameters.' It specifies the verb ('retrieves'), resource ('time series data'), and source ('FSI database'). However, it doesn't explicitly differentiate from sibling tools like fetch_bop_data or fetch_ifs_data, which likely retrieve different datasets from similar databases.

  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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or explain what makes FSI data distinct from other datasets like BOP or CPI data. The only usage hint is in the Returns section about not retrying on failure, but this doesn't help with tool selection.

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

• fetch_mfs_dataB
  3.3/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It discloses that the tool retrieves data (implying a read-only operation) and includes a behavioral note about not performing further analysis or retry on failure, which is valuable. However, it doesn't mention potential rate limits, authentication needs, or data format specifics, leaving gaps in behavioral context.

  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 purpose statement, Args section, and Returns section, making it easy to parse. It's appropriately sized with no redundant information, though the 'Returns' note about not performing analysis could be integrated more smoothly.

  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 5 parameters with 0% schema coverage and no output schema, the description does a decent job explaining parameters and return behavior. However, it lacks context about the MFS database, sibling tool relationships, and error handling details, making it minimally adequate but with clear gaps for a data retrieval tool.

  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%, so the description must compensate. It provides clear semantics for all 5 parameters (e.g., 'freq' with example 'A' for annual, 'country' with multiple codes connected by '+'), adding essential meaning beyond the bare schema. This effectively documents parameter usage, though it could benefit from more examples or constraints.

  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 the action ('Retrieves') and resource ('compact format time series data from the MFS database'), making the purpose evident. It distinguishes itself from siblings like list_countries or list_indicators by focusing on data retrieval rather than metadata listing, though it doesn't explicitly differentiate from other fetch_* tools that likely retrieve different datasets.

  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?

  No guidance is provided on when to use this tool versus alternatives like other fetch_* tools (e.g., fetch_bop_data, fetch_ifs_data). The description lacks context about the MFS database scope or prerequisites, leaving the agent to infer usage based on tool names alone.

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

• fetch_cpis_dataA
  3.5/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal that the tool returns 'compact format time series data' and includes a warning about query failures ('Do not perform further analysis or retry if the query fails'). However, it doesn't disclose important behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or what happens with invalid parameters. The warning about query failures is helpful but incomplete.

  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 clear sections (purpose, Args, Returns) and every sentence adds value. The parameter explanations are efficient yet informative. The only minor inefficiency is the slightly redundant 'based on the input parameters' in the first sentence, but overall this is appropriately sized and front-loaded with the core purpose.

  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?

  For a 6-parameter data retrieval tool with no annotations and no output schema, the description provides good parameter documentation but has significant gaps. It doesn't explain the return format beyond 'compact format time series data' or what 'Description of the queried data' means. The warning about query failures is helpful but doesn't specify what constitutes failure or error conditions. Given the complexity and lack of structured metadata, the description should do more to explain behavioral expectations.

  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?

  Given that schema description coverage is 0% (all parameters have only titles with no descriptions), the description provides excellent parameter semantics. It clearly explains each of the 6 parameters with examples and formatting rules (e.g., 'multiple country codes can be connected with "+"'). This fully compensates for the lack of schema descriptions and gives the agent meaningful guidance on how to use each parameter correctly.

  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 the tool's purpose: 'Retrieves compact format time series data from the CPIS database based on the input parameters.' This specifies the action (retrieves), resource (time series data from CPIS database), and format (compact format). However, it doesn't explicitly differentiate this CPIS data tool from its sibling tools (like fetch_bop_data, fetch_cdis_data, etc.), which appear to retrieve different datasets from the same system.

  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 provides no guidance on when to use this tool versus its siblings. While the name suggests it's for CPIS data (Coordinated Portfolio Investment Survey), there's no explicit comparison or differentiation from tools like fetch_bop_data (Balance of Payments) or fetch_cdis_data (Coordinated Direct Investment Survey). The description also lacks information about prerequisites, error conditions, or alternative approaches.

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

• fetch_ifs_dataA
  3.5/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves data (implying read-only) and includes a behavioral note in the Returns section: 'Do not perform further analysis or retry if the query fails.' This adds useful context about error handling. However, it doesn't mention other important behaviors like rate limits, authentication needs, or data format specifics, leaving gaps for a tool with 5 parameters.

  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 and appropriately sized. It starts with a clear purpose statement, then lists parameters with helpful details, and ends with return behavior guidance. Every sentence adds value, though the 'Returns' section could be integrated more smoothly. It's front-loaded with the core functionality, making it efficient for an agent to parse.

  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 tool's complexity (5 parameters, no annotations, no output schema), the description is moderately complete. It covers parameter semantics thoroughly and includes error-handling guidance, which is valuable. However, it lacks details on output format (beyond 'description of the queried data'), potential side effects, or how it differs from sibling tools, leaving some gaps for a data retrieval tool in a family of similar tools.

  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 description provides excellent parameter semantics beyond the schema, which has 0% description coverage. It explains each parameter's purpose: 'freq' with an example ('A' for annual), 'country' with format details (multiple codes with '+'), 'indicator' as a code, and 'start'/'end' as years. This fully compensates for the schema's lack of descriptions and gives the agent clear guidance on how to use each 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 clearly states the tool's purpose: 'Retrieves compact format time series data from the IFS database based on the input parameters.' It specifies the verb ('Retrieves'), resource ('time series data'), and source ('IFS database'), which is clear and specific. However, it doesn't explicitly differentiate from sibling tools like fetch_bop_data or fetch_cpis_data, which likely retrieve different types of data from the same database.

  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 provides no guidance on when to use this tool versus its siblings. While it mentions retrieving 'compact format time series data,' it doesn't explain what distinguishes this from other fetch_* tools (e.g., fetch_bop_data for balance of payments data). There's no mention of prerequisites, alternatives, or exclusions, leaving the agent with minimal context for tool selection.

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

• fetch_bop_dataA
  3.6/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It discloses that data is retrieved in 'compact format' and includes a behavioral note in the Returns section: 'Do not perform further analysis or retry if the query fails.' This adds useful context about error handling. However, it doesn't mention rate limits, authentication needs, or what happens with invalid parameters, leaving gaps for a tool with 5 required parameters.

  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 well-structured and appropriately sized. It starts with a clear purpose sentence, followed by an Args section with bullet-like parameter explanations, and ends with a Returns section. Every sentence adds value, with no wasted 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 5 required parameters, no annotations, and no output schema, the description does a decent job but has gaps. It explains parameters well and includes a behavioral note on failure handling. However, it doesn't describe the return format beyond 'description of the queried data' (vague), and lacks context on data scope or limitations. For a data retrieval tool with multiple siblings, more differentiation would help.

  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 compensate fully. It provides detailed semantics for all 5 parameters: freq with examples ('A' for annual), country with format details (multiple codes with '+'), indicator as a code, and start/end as years. This adds significant meaning beyond the bare schema, effectively documenting parameter usage.

  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 the tool 'retrieves compact format time series data from the BOP database based on input parameters,' which specifies the verb (retrieves), resource (time series data from BOP database), and format (compact). However, it doesn't explicitly differentiate from sibling tools like fetch_cdis_data or fetch_ifs_data, which likely retrieve similar data from different databases.

  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 provides no guidance on when to use this tool versus its siblings (e.g., fetch_cdis_data, fetch_ifs_data). It mentions 'based on input parameters' but doesn't clarify what makes BOP data distinct or when to choose this over alternatives. The only usage hint is in the Returns section about not retrying on failure, but this doesn't address tool selection.

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