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get_methodology

Returns SaaSDossier's two-state evidence framework: Documented and Question surfaced. A Question surfaced is not a finding of absence. SaaSDossier is the vendor's own record, made reviewable: a finished, dated, source-linked, human-reviewed evidence workproduct built only from vendor-published sources, recording 55 fixed fields across 10 domains for each vendor, with a source register listing every vendor page reviewed. Documented means the reviewed vendor-published sources established the field for the evidence date; Question surfaced means they did not, and each one becomes a buyer-ready follow-up question. Each dossier includes a SHA-256 identifier tied to the reviewed evidence record used for that release. Use this tool to understand what a state means, what the framework covers and where its boundaries are, before quoting or acting on any field.

Input Schema

TableJSON Schema
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TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of disclosure. It goes into significant detail about behavioral nuances: 'Question surfaced is not a finding of absence,' definitions of Documented and Question surfaced, the nature of SaaSDossier as a vendor-published-source-based workproduct, the 55 fields across 10 domains, source register, and SHA-256 identifier. This is rich, explicit context beyond the tool name.

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?

Though the description is lengthy, every sentence adds substantive content: it defines the two-state framework, clarifies what Question surfaced is not, explains the underlying SaaSDossier artifact, describes coverage details, and gives usage guidance. It is front-loaded with the core return value and organized logically, avoiding fluff.

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 conceptual nature and lack of input/output schemas, the description provides everything an agent needs to correctly interpret states and decide when to invoke the tool. It explains the framework's boundaries, the meaning of each state, the source basis, and the evidence date, making it fully self-contained.

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 tool accepts zero parameters, and the schema confirms this with additionalProperties false and no properties. The 0-parameter baseline applies; the description does not need to explain parameter behavior. It focuses entirely on the output/behavior, which is appropriate for a parameterless tool.

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 opens with a specific verb+resource: 'Returns SaaSDossier's two-state evidence framework.' It clearly explains the framework's two states and distinguishes this tool from siblings that return dossiers, ledgers, or registers by focusing on the methodology itself.

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?

It explicitly says to 'Use this tool to understand what a state means, what the framework covers and where its boundaries are, before quoting or acting on any field,' which gives clear context for when it should be used. It does not name alternative tools or explicitly state when not to use it, but the purpose is well differentiated from the sibling tools.

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

A4.4/5.0
Disambiguation4/5

The four tools mostly have clear boundaries: methodology, register, ledger, and free dossier are conceptually distinct. However, get_free_dossier and get_openai_ledger both point at the same public OpenAI record, and an agent must read carefully to know one returns a PDF/URL and the other field-level evidence.

Naming Consistency5/5

All tool names follow a consistent get_ pattern with clear object nouns: dossier, methodology, openai_ledger, register. There is no mixed casing, verb style variation, or vagueness across the set.

Tool Count5/5

Four tools is a well-scoped size for an informational evidence ledger service: methodology, the public ledger, the free dossier, and the release register. Each tool earns its place and the set does not feel thin or bloated.

Completeness4/5

The core workflow is covered: understand the framework, access the free public dossier, retrieve field-level evidence, and view releases and commission options. The main gap is that licensed dossiers are described in the register but cannot be fetched directly, and commissioning is reported but not executable through a tool.

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