Server Quality Checklist

Tool Scores

• get_individual_assessmentsB
  3.1/5.0
  Behavior2/5

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

  No annotations are present, so the description must convey behavioral traits. It only states what is returned, with no mention of side effects, authentication, file existence handling, or read-only nature. Minimal transparency.

  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 concise: a one-line purpose then a short Args list. It is front-loaded with the main action and result fields. No redundant sentences.

  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 simplicity (2 params, output schema present), the description covers the basic functionality and return fields. However, it lacks usage guidance and behavioral context, making it minimally complete.

  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. The Args section adds brief explanations ('LNA CSV file path', 'team setting JSON (optional)') but lacks detail on formats, defaults, or constraints. For two parameters, 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?

  Description clearly states it returns individual competency assessment results and lists the specific fields (name, team, average score, strengths, weaknesses, recommended trainings). The verb 'returns' and explicit resource make 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 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 vs. its siblings (analyze_lna, get_team_scores, etc.). The description does not indicate scenarios or alternatives, leaving the agent to guess.

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

• generate_reportB
  3.3/5.0
  Behavior3/5

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

  No annotations provided, so description carries full burden. It discloses the core behavior (analyze CSV, output PPT) but omits side effects, permissions, error handling, or constraints. With no annotations, a score of 3 reflects minimal but adequate behavioral disclosure for a report-generation 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 concise with a single introductory sentence and a structured Args block. Every sentence adds value, though the Args section could be slightly more compact. Overall efficient.

  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, return values need not be explained. However, the description lacks context about input CSV format, error scenarios, and report content scope. With 4 parameters and no annotations, some completeness gaps remain.

  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 0%, so description must add meaning. The Args section provides clear descriptions for all 4 parameters, including an example for 'team_config' and default values for optional params. This compensates well for 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 generates a PPT report from LNA CSV data. It uses a specific verb-resource pairing ('analyzes and generates') and implies a distinct purpose from sibling tools like 'analyze_lna' and 'get_individual_assessments', though not explicitly differentiating.

  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 on when to use this tool versus alternatives. The description only states what it does, not when it should be selected over siblings like 'analyze_lna' or 'get_recommendations'. No exclusions or prerequisites are mentioned.

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

• get_recommendationsB
  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 burden. It discloses the tool returns recommendations based on a CSV file and optional team name, but does not mention side effects, permissions, or error conditions. It is adequate for a simple read operation but lacks depth.

  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?

  Extremely concise: three lines with a clear front-loaded Korean sentence. Every phrase is necessary with no wasted words. Efficient communication.

  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 an output schema exists (not shown), the description need not detail return values. However, it does not explain the nature of recommendations, how the CSV is used, or any dependencies. Minimal but sufficient for a simple tool with few parameters.

  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 0%, so description adds meaning. It explains csv_path as 'LNA CSV file path' and team_name as 'team name (empty for all)'. This adds context beyond the schema titles, though examples or format constraints would improve it.

  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 returns team-specific training recommendations (verb+resource). It distinguishes from siblings like get_individual_assessments and get_team_scores by focusing on recommendations. However, it could be more specific about the source (LNA CSV) and the context of 'education recommendations'.

  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 explicit guidance on when to use this tool versus alternatives (e.g., analyze_lna, generate_report). The description does not mention scenarios, prerequisites, or when not to use it.

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

• get_team_scoresA
  3.5/5.0
  Behavior2/5

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

  No annotations are provided, so the description must fully disclose behavior. It only states that scores are returned, but omits details such as error handling for invalid csv_path, performance implications, or what 'competency scores' entail.

  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—two sentences plus parameter documentation—with the purpose stated upfront. 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?

  The tool has an output schema, so the description does not need to detail returns. However, it lacks context on behavioral aspects (e.g., data format, error behavior) and does not explain how team_name interacts with the CSV. Adequate but with 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%, but the description adds meaningful context: csv_path is the 'LNA CSV file path' and team_name defaults to all teams when empty. This clarifies the parameters beyond the schema's minimal titles.

  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 returns competency scores by process for a specific team or all teams. It uses a specific verb ('returns') and resource ('competency scores'), and distinguishes from siblings that focus on individual assessments or analysis.

  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 get_individual_assessments or get_recommendations. It merely states what it does without indicating context or exclusions.

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

• analyze_lnaA
  3.7/5.0
  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. It explains the purpose and parameters but does not disclose side effects (e.g., read-only or mutating), error handling, or output format details beyond the implied return of team capability status.

  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 and front-loaded with the core purpose. The Args section is cleanly structured with no superfluous text.

  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 presence of an output schema, the description adequately covers tool usage and parameter semantics. Minor gap: the expected CSV format is not described, but overall it is complete for correct invocation.

  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?

  With 0% schema description coverage, the description effectively documents both parameters. It gives a clear definition for csv_path (LNA CSV file path) and team_config (optional JSON string with example), adding essential meaning beyond the schema's type and title.

  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 analyzes LNA CSV files to return team capability status. This distinguishes it from siblings like generate_report (creates a report) and get_individual_assessments (focuses on individuals).

  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 prerequisites or exclusions, leaving the agent to infer context.

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