Get all specifications referenced by a given spec.
Args:
spec_number: Specification number (e.g., "23.501", "26.230")
reference_type: Filter by type - "normative", "informative", "inline" (optional)
| Name | Required | Description | Default |
|---|---|---|---|
| spec_number | Yes | ||
| reference_type | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It does not mention that the operation is read-only, what happens with invalid spec numbers, whether references are returned recursively, or any pagination/result limits. The description only covers the basic operation and filter options, leaving the agent without important 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. It delivers a clear one-sentence purpose, followed by a compact Args section that lists and explains the parameters. Every sentence is informative and there is no wasted wording, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with an output schema present, the description covers the core purpose and parameter details effectively. It does not explain return values, but the output schema handles that. The main gap is the lack of usage guidance, which is already penalized in dimension 2. Overall, the description is fairly complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides only type and title for both parameters, with zero description coverage. The description adds valuable semantics by giving example spec numbers ('23.501', '26.230') and enumerating possible reference_type values ('normative', 'informative', 'inline'). This compensates well for the schema's lack of detail, though it does not explain the meaning or behavior of these types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get all specifications referenced by a given spec.' It uses a specific verb and resource, and includes example spec numbers for clarity. However, it does not distinguish itself from sibling tools like get_spec_dependents or get_relationship_graph, so it lacks explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. The description simply states what the tool does without any context about suitable scenarios, exclusions, or preferred use cases. For instance, it does not mention that this tool is for outgoing references and get_spec_dependents for incoming references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Tools are largely distinct but there are clusters of similar functionality, such as multiple search mechanisms (search_specifications, semantic_search, get_requirements with a search parameter) and reference-graph tools (get_spec_references, get_spec_dependents, get_relationship_graph). Descriptions do differentiate them, but an agent could still be uncertain which to use for a given query.
Most tool names follow a snake_case verb_noun pattern (e.g., list_documents, search_specifications, get_requirements). However, semantic_search is adjective_noun rather than verb_noun, and get_database_stats is a generic outlier among the spec-focused tools. Overall the pattern is consistent with minor deviations.
With 17 tools, the set is slightly above the ideal 3-15 range but not excessive for the breadth of functionality: search, metadata, requirements, test generation, relationships, and schemas. Each tool has a defined role, and the count feels warranted for the domain.
The tool set covers the core workflow well: discovering specs (search_specifications, list_documents), retrieving content (get_document_content, get_requirements), analyzing relationships (get_spec_references, get_spec_dependents), and generating tests (build_cross_spec_suite, generate_tests). Minor gaps exist, such as the lack of a direct tool to fetch a requirement's full surrounding clause (workaround via get_document_content), but no critical dead ends.