Server Quality Checklist

Tool Scores

• analyze_urlA
  4.6/5.0
  Behavior5/5

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

  With no annotations provided, the description comprehensively covers side effects, authentication, rate limits, error handling, idempotency, and data privacy in a dedicated section. This fully compensates for the lack of 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 well-structured with clear headings and sections, but it is somewhat verbose and repeats behavioral transparency information in both a list and a block. It is front-loaded with the main purpose and remains readable.

  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 no output schema, no annotations, and no schema descriptions, the description is highly complete. It covers behavior, error handling, rate limits, authentication, and privacy, leaving no critical gaps for an AI agent to understand the 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 coverage is 0% (no descriptions in schema). The description provides brief explanations for each parameter (url, api_key) in the Args section, adding some meaning beyond the schema, but does not elaborate on formats, constraints, or defaults. This partially compensates but could be more detailed.

  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 'Check a URL for phishing indicators and suspicious patterns,' which is a specific verb and resource. It clearly distinguishes from sibling tools like detect_social_engineering or verify_sender by focusing on URL phishing analysis.

  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?

  Explicitly provides 'When to use' (structured analysis against frameworks) and 'When NOT to use' (not for real-time production without human review), offering clear context and exclusions.

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

• detect_social_engineeringA
  4.6/5.0
  Behavior5/5

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

  Despite no annotations, the description fully covers side effects (read-only, stateless), authentication, rate limits, error handling, idempotency, and data privacy. Provides comprehensive behavioral disclosure.

  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?

  Well-structured with clear sections, but somewhat lengthy. Every sentence adds value, though could be tighter. Front-loads core purpose.

  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 no output schema and no annotations, the description covers purpose, usage, parameters, and behavioral aspects thoroughly. Includes rate limits, error handling, and idempotency—complete for informed use.

  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 compensates by explaining the 'conversation' parameter as text to analyze and 'api_key' as optional for pro tier. Adds meaningful context beyond schema types.

  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 detects manipulation tactics using Cialdini's principles in conversations, with a specific verb and resource. It distinguishes from sibling tools like analyze_url and verify_sender which handle different tasks.

  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?

  Explicit 'When to use' and 'When NOT to use' sections provide clear context for structured analysis vs. production decision-making. Lacks direct comparison to siblings, but sibling purposes are distinct enough.

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

• quick_checkA
  4.9/5.0
  Behavior5/5

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

  Detailed behavioral transparency section covering side effects, authentication, rate limits, error handling, idempotency, and data privacy. Exceeds what annotations would provide.

  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?

  Well-structured with clear headings, front-loaded purpose, and efficient use of text. Every sentence adds value.

  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?

  Covers all necessary aspects: purpose, usage guidelines, behavioral details, and parameter semantics. No gaps for a simple analysis 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?

  Single parameter 'message' is clearly described as the input text. Although schema lacks description, the tool description adds meaningful context about the parameter's role.

  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?

  Clearly states the tool provides a scam probability score for messages (email, text, DM). Differentiated from siblings like analyze_url which handles URLs.

  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?

  Explicit 'When to use' and 'When NOT to use' sections guide appropriate usage, including caveats about real-time decisions and rate limits.

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

• report_scamA
  4.9/5.0
  Behavior5/5

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

  No annotations are provided, so the description bears full responsibility. It thoroughly discloses side effects (read-only, stateless, idempotent), authentication (none required for basic, optional API key for pro), rate limits (10/day free, unlimited pro), error handling (structured errors), and data privacy (no storage). This exceeds expectations.

  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 sections (Args, Behavior, When to use, Behavioral Transparency) but contains some redundancy between the Behavior and Behavioral Transparency sections. It is front-loaded with purpose, but could be slightly more concise without losing information.

  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 complexity and lack of annotations, the description covers all essential aspects: purpose, parameters, behavioral traits, error handling, and privacy. It adequately compensates for the missing output schema by stating the tool produces analysis output in-memory.

  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. It explicitly describes the 'description' parameter as 'Description of the scam including the message, sender, and what happened.' and 'api_key' as 'Optional MEOK API key for pro tier.' This adds meaningful guidance beyond the bare 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 'Log and analyze a scam report. Contributes to collective threat intelligence.' This defines a specific verb (log and analyze) and resource (scam report). It distinguishes from sibling tools like 'analyze_url' and 'verify_sender' which handle different input types.

  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 includes explicit 'When to use' and 'When NOT to use' sections, providing clear context and exclusions. It advises use for structured analysis and warns against real-time production decisions without human review, which helps the agent decide appropriately.

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

• verify_senderA
  4.9/5.0
  Behavior5/5

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

  With no annotations, the description fully covers behavioral traits: read-only, stateless, idempotent, rate limits, authentication, error handling, and data privacy. No contradictions.

  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?

  Well-structured with sections, front-loaded purpose, and minimal redundancy. Slightly lengthy but all sentences add value.

  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?

  Despite no output schema and only 2 parameters, the description provides comprehensive context: behavior, limitations, error handling, and privacy, ensuring the agent can use 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 adds meaning for both parameters: email_or_phone 'The email address or phone number to check' and api_key 'Optional MEOK API key for pro tier,' compensating fully.

  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 'Check sender patterns against known scam vectors,' specifying the verb (check) and resource (sender patterns) and differentiates it from sibling tools like analyze_url and detect_social_engineering.

  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?

  Explicit 'When to use' and 'When NOT to use' sections provide clear guidance: use for structured analysis against frameworks, not for real-time production without human review.

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