Server Quality Checklist

Tool Scores

• sync_ai_platform_stateC
  2.4/5.0
  Behavior2/5

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

  No annotations are provided, so the description must convey behavioral traits. It mentions 'verifies and synchronizes', implying mutation, but does not disclose side effects, auth requirements, or error conditions. The description is insufficient for an AI to anticipate behavior.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness2/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single sentence, but it lacks substance. It front-loads the resource but fails to provide necessary details, making it under-specified rather than concise.

  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 the four parameters, three required, and no annotations, the description is inadequate. An output schema exists, so return values need not be described, but the description still fails to cover parameter usage, triggers, or limitations.

  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%, and the description does not explain any of the four parameters (student_id, current_level, interval_days, platform_token). No meaning beyond the schema's type and title is added.

  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 action ('verifies and synchronizes') and resource ('student progress with external platforms'). However, it does not differentiate from sibling tools like 'sync_lms_onboarding_state', which share a similar purpose.

  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 such as 'calculate_spaced_repetition' or 'sync_lms_onboarding_state'. The description lacks explicit context for selection.

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

• generate_skills_assessmentC
  2.7/5.0
  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 only notes 'strictly mapped' behavior but omits other traits such as mutability, auth requirements, or side effects. Insufficient disclosure 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Single sentence with no extraneous words. Every part contributes to the core purpose. Ideal conciseness.

  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?

  Despite having an output schema, the description fails to describe return format or behavior. With 3 undocumented parameters and no annotations, the tool is underspecified for reliable use. The description is too short to be complete.

  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 parameter-level meaning. Parameters like 'subject_segment', 'target_level', and 'cognitive_dimension' are not explained, leaving the agent with no guidance beyond names.

  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 questions mapped to Bloom's Taxonomy cognitive dimensions, using a specific verb and resource. It distinguishes itself from unrelated sibling tools, but lacks further specificity about question type or domain.

  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 does not mention context, prerequisites, or exclusions, leaving the agent to infer usage independently.

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

• sync_lms_onboarding_stateC
  2.9/5.0
  Behavior2/5

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

  No annotations provided, so description must disclose all behavioral traits. It mentions parsing, scheduling, and payload generation but does not indicate side effects, authentication needs, or whether state is mutated.

  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?

  Two sentences with no extraneous words. However, for a complex tool, a bulleted list or structured overview could improve readability.

  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?

  Despite having an output schema, the description lacks prerequisites, error handling, and return value summary. Six required parameters demand more context for correct invocation.

  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 has 6 parameters with 0% description coverage. The description only loosely maps quiz_score_pct to 'raw SCORM quiz scores' and implies SM-2 parameters but does not explain lms_student_id, scorm_package_id, or others.

  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 integrates with Moodle/Canvas, parses SCORM scores, executes SM-2 scheduling, and outputs a signed LTI payload. This distinguishes it from siblings like calculate_spaced_repetition and sync_ai_platform_state.

  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. The description provides high-level functionality but lacks conditions for use or exclusions.

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

• calculate_spaced_repetitionB
  3.3/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It mentions the use of a well-known algorithm (SM-2), implying a deterministic calculation without side effects, but does not explicitly state idempotency, destructive potential, or other behavioral traits. A score of 3 reflects adequate but 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 a single sentence with no extraneous information. It is concise but could benefit from slight expansion to cover parameter roles. However, it is adequately sized for a simple calculation tool.

  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?

  An output schema exists, so return value explanation is unnecessary. However, the description lacks details on algorithm assumptions, edge cases, or parameter validation, which may be needed given the tool's mathematical nature. The description is minimally complete for a known algorithm but not fully self-contained.

  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?

  The schema coverage is 0% and the description does not explain any of the four required parameters (grade_1_5, repetition_count, previous_ease_factor, previous_interval_days). The algorithm name provides indirect context that these are standard SM-2 inputs, but the description fails to add explicit meaning or constraints beyond the schema's 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 calculates the next optimal review date using the standardized SM-2 algorithm. It specifies a unique verb ('calculates'), resource ('next optimal review date'), and method, distinguishing it from sibling tools which deal with assessment and syllabus generation.

  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, nor any prerequisites or contextual clues. Without explicit usage context, an AI agent may not understand the appropriate scenarios for invoking this tool.

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

• get_progressive_syllabusA
  3.5/5.0
  Behavior3/5

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

  The description notes the output is 'exact deterministic', which is a behavioral trait beyond annotations (none provided). However, it omits details like permissions, side effects, or response format, which are important given 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single concise sentence with no wasted words. It is appropriately front-loaded and sufficient for a simple tool.

  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 has two parameters, one required, and no annotations, the description could be more complete. It fails to mention 'subject_segment' and does not describe the return value despite having 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?

  Schema description coverage is 0%, so the description must compensate. It links 'current_mastery_level' to the student's mastery level, but does not explain 'subject_segment', a required parameter. Partial compensation.

  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 retrieves a lesson plan based on mastery level, using specific verbs and resource. It distinguishes from siblings which involve calculations, assessments, or sync operations.

  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 like calculate_spaced_repetition or generate_skills_assessment. The description does not provide context for selection.

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