Server Quality Checklist

Tool Scores

• get_agnifolio_infoB
  3.3/5.0
  Behavior2/5

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

  No annotations are present, so the description carries full responsibility. It describes the tool's subject matter but does not disclose what happens when called (e.g., returns documentation, requires no side effects, output format). This is a significant gap for a tool with no annotations.

  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 a single sentence that efficiently lists three key aspects of the tool's content. It is appropriately short and front-loaded, though it could be slightly more structured with separators.

  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 zero-parameter, no-output-schema tool, the description provides a reasonable high-level overview. However, it does not specify the form of the information returned (e.g., text, structured data) or depth of content, leaving some uncertainty for an AI agent.

  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 tool has zero parameters, and the schema already reflects this with 100% coverage. No parameter semantics are needed, and the description appropriately says nothing about parameters. Baseline for 0 params is 4.

  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 provides information about Agni Folio, the public server's capabilities, and OAuth connection guidance. It distinguishes from sibling tools that focus on specific financial calculations, though it lacks an explicit verb like 'returns'.

  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 the tool is for users wanting to understand the platform and how to connect an AI to a portfolio. It does not explicitly state when to use it vs. alternatives or any exclusions, but the context ('public server', 'hosted OAuth') suggests an overview role.

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

• find_networth_percentileA
  3.8/5.0
  Behavior3/5

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

  No annotations are provided, so the description must carry the burden. It discloses the data source and optional segments, but does not explain default behavior when across_world is false and no countries are provided, nor the return format. This is adequate but with notable gaps.

  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 a single, well-structured sentence that front-loads the action and scoping, with no wasted words. It is efficient and easy to parse.

  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?

  The tool has 6 parameters and no output schema, so the description needs to explain return values and default behavior. It mentions the dataset but does not explain what happens when across_world is false and no countries are given, nor what the output percentile looks like. This is a significant gap for an agent.

  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 covers 100% of parameters, so the baseline is 3. The description adds context by mapping 'globally or within specific countries' to across_world/countries and 'segmented by age and gender' to age/gender, but adds no syntax or format details beyond the 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 uses the specific verb 'Find' and clearly identifies the resource: net worth percentile, with scope (global/countries) and optional segments. It is distinct from siblings like calculate_fire_number, which addresses different use cases.

  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?

  It clearly indicates the tool is for percentile lookups and mentions global vs country scoping, implying when to use it. However, it doesn't explicitly name alternative tools or state exclusions, so it stops short of a 5.

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

• get_high_interest_productsA
  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 carries the transparency burden. It discloses that data is community-verified and from a public database, and that results include rates and conditions. However, it does not describe return format, sorting, or whether the data updates automatically, leaving some behavioral aspects ambiguous.

  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 a single, focused sentence that immediately states the tool's purpose, scope, and data source. Every word adds value and there is no fluff or repetition.

  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 low complexity and full schema coverage, the description covers the main aspects: geography, product types, and data provenance. It doesn't mention default behavior when no filters are applied, but that is implicit in the schema. Overall, it is sufficiently complete for a simple list endpoint without an output schema.

  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 input schema already provides 100% coverage for both parameters (country and product_type), each with descriptions. The tool description adds no additional parameter detail, so it neither compensates nor detracts from the schema. Baseline 3 is appropriate.

  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 lists high-interest savings accounts, fixed deposits, and treasury products across specific countries (Singapore, India, USA), with rates and conditions. The verb 'List' is specific and the resource is well-defined, distinguishing it from siblings like calculate_fire_number or find_networth_percentile.

  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 clear context for when to use the tool: when needing current high-interest product rates across the mentioned countries. It does not explicitly mention alternatives or exclusions, but the context is unambiguous given the sibling tools serve different purposes.

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

• calculate_fire_numberA
  4.4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the disclosure burden. It adds meaningful behavioral context: 'pure local math, no data leaves the machine' indicates a privacy-safe, deterministic operation. It also discloses conditional output behavior based on optional parameters, though it could mention error/edge cases.

  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 well-structured sentences: the first conveys the core function and conditional outputs, the second adds a privacy guarantee. No redundant information; every word serves a purpose, and the main verb appears immediately.

  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 7-parameter tool with no annotations or output schema, the description covers the core calculation, conditional extensions, and privacy. It lacks explicit return format details or edge-case handling, but the domain is simple enough that the description provides a reasonably complete picture.

  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 by explaining parameter interactions (e.g., annual expenses + withdrawal_rate yield base FIRE; adding net worth/savings/return gives progress and years). This goes beyond individual schema descriptions and helps the agent understand how parameters combine.

  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 calculates a FIRE number from explicit inputs (annual expenses, withdrawal rate) and extends to progress metrics when additional data is provided. It distinguishes itself from sibling tools (info/percentile lookups) by focusing on financial calculation, making the purpose unambiguous.

  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 implicitly defines when to use the tool (for FIRE calculations) and explains that optional parameters enable advanced outputs. It doesn't explicitly mention alternatives or exclusions, but the sibling tools are topically distinct, making the usage context clear without needing direct comparisons.

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