Server Quality Checklist

Tool Scores

• fedramp_list_documentsA
  4.2/5.0
  Behavior4/5

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

  Annotations already indicate read-only and idempotent behavior. Description adds context on optional filtering and return format, which goes beyond what annotations provide.

  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 a summary sentence, usage context, section list, and clear Args/Returns sections. Slightly verbose with the section list but overall efficient.

  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?

  Covers input parameters and output format thoroughly. Lacks mention of pagination or limits, but for a browsing tool this is acceptable.

  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?

  Description explicitly explains both parameters (section and response_format) with types and defaults, compensating for the 0% schema description coverage.

  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 verb 'List' and resource 'documents in the corpus', with optional filtering by section. Distinguishes from sibling tools that get specific documents or search.

  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?

  Provides a hint on when to use ('browsing the structure before drilling in') and lists sections, but does not explicitly state when not to use or compare to alternatives.

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

• fedramp_get_definitionA
  4.3/5.0
  Behavior4/5

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

  Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and description adds that it returns actionable error with suggestions if term not found, and case-insensitive matching. 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.

  Conciseness5/5

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

  Two concise paragraphs with front-loaded purpose, followed by authoritative context and parameter/return details. Every sentence is necessary and informative without redundancy.

  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?

  For a simple lookup tool with one parameter and an output schema present, the description fully covers input format, authoritative nature, return structure (definition, ID, aliases, related terms), and error handling. No gaps.

  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 has a clear description for the 'term' parameter (e.g., examples and case-insensitivity), so the tool description adds only marginal extra context (e.g., 'FRD ID', 'alias'). Schema description coverage is reported as 0% but property descriptions exist; assuming actual coverage is higher.

  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 looks up a FedRAMP defined term by name, alias, or FRD ID. It distinguishes from siblings like 'fedramp_get_document' (for documents) and 'fedramp_get_rule' (for rules) by focusing solely on definitions.

  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?

  Explicitly notes that definitions are authoritative and part of the rule, giving context for when to use. Provides example inputs and explains return behavior, though does not explicitly list alternatives for when not to use.

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

• fedramp_get_ruleA
  4.3/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds value by specifying that all occurrences are returned, the format is Markdown, and errors include close ID suggestions. This goes beyond the annotations, though it doesn't discuss other behaviors like rate limits or authentication.

  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 brief but information-dense: a one-sentence purpose, followed by examples of ID formats, and clear return/error behavior. It is well-structured and front-loaded, with no wasted words.

  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 simplicity (one parameter), complete annotations, and the presence of an output schema, the description covers all essential aspects: what the tool does, ID formats, return content, and error handling. It is fully sufficient for an agent to use correctly.

  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 provides a description for rule_id (including case-insensitivity and examples), and the tool description repeats similar info. With 100% schema coverage (the schema description is non-empty), the description adds marginal value beyond the schema, warranting a baseline of 3.

  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 specifies 'Retrieve a rule (or NIST control) by its ID, with every place it appears.' It contrasts with sibling tools (e.g., fedramp_search) by focusing on retrieval by known ID and returning all occurrences, making its purpose distinct.

  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 explains when to use: when you have a known FedRAMP or NIST control ID and need all occurrences across documents. Examples of IDs are given, but it doesn't explicitly state when not to use (e.g., for searching unknown IDs) or mention alternatives like fedramp_search.

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

• fedramp_get_documentA
  4.5/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds that it returns markdown with frontmatter stripped and an actionable error for unknown paths, providing useful 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.

  Conciseness5/5

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

  Very concise and well-structured. The first sentence states the purpose, followed by usage guidance and parameter details. No unnecessary words.

  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?

  The description adequately covers input, output format, and error handling. Given the presence of an output schema and clear annotations, the description is complete for this 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?

  The description explains the parameter path with type, format, and example in the Args section. The input schema also contains a description, so this adds value 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 clearly states it returns the full markdown of one FedRAMP document by its path. It distinguishes itself from sibling tools like fedramp_search and fedramp_list_documents by specifying the action and input.

  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?

  Provides explicit guidance: use a path from fedramp_search or fedramp_list_documents. Does not explicitly mention when not to use it, but context is clear.

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

• fedramp_searchA
  4.8/5.0
  Behavior5/5

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

  Annotations already declare read-only and idempotent behavior. The description adds details about BM25 ranking, output format, snippet generation, and the 'No matches' response, all consistent with 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?

  Well-structured with front-loaded purpose and usage, but slightly verbose with detailed args/returns. Could be trimmed slightly without losing clarity.

  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?

  Comprehensively covers the search behavior, ranking, filtering, output formats, error handling, and links to sibling tools. Complete for a search tool with two output modes and multiple 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?

  Though the schema has basic descriptions, the overall param description coverage is 0% for the top-level 'params' parameter. The description compensates by explaining each parameter's purpose, accepted formats (e.g., 'keywords or a rule ID'), and defaults.

  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 performs full-text search across the FedRAMP rules corpus, specifies the verb and resource, and distinguishes from siblings by mentioning follow-up tools like fedramp_get_document.

  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 tells when to use this tool (initial search) and when to use alternatives (fedramp_get_rule, fedramp_get_document) for retrieving specific items, providing clear guidance on the workflow.

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