SpecProof

Get Requirements

get_requirements

Read-onlyIdempotent

List normative requirements (RFC 2119 / BCP 14 "shall/should/may" statements) extracted from specifications, each cited back to its source clause.

Args:
    spec_number: Filter by spec number, e.g. "23.501" or "RFC 9110" (optional)
    obligation: Filter by strength - "must", "must_not", "should", "should_not", or "may" (optional)
    search: Keyword to search within the requirement text (optional)
    limit: Maximum number of requirements to return (default: 30, max: 100)

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`search`	No
`obligation`	No
`spec_number`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare read-only and idempotent behavior, so the description adds value by explaining that each requirement is 'cited back to its source clause' and by documenting the default and maximum limit. This goes beyond the annotations without contradicting them.

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 well-structured: a single-sentence purpose followed by a clean Args list. Every line adds value, no fluff.

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 output schema exists and all parameters are fully documented, the description is quite complete. It covers the key behavior of citing source clauses and the filtering options, though it doesn't explicitly state the return type or error handling, which are likely covered by the output schema.

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 fully compensates by explaining each parameter in detail, including examples for spec_number, allowed values for obligation, and default/max for limit. This adds significant meaning 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 uses the specific verb 'List' and clearly identifies the resource as 'normative requirements extracted from specifications, each cited back to its source clause.' This distinguishes it from sibling tools like search_specifications or get_document_content, which serve different purposes.

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?

The description implies usage by focusing on listing normative requirements, but it does not explicitly compare with alternatives or state when not to use this tool. Given the distinct purpose, it's clear enough, but there's no explicit when/when-not guidance.

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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TDQS

A3.8/5.0

Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count4/5

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.

Completeness4/5

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.

Resources

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