Return aggregate-only counts of the droplinked trust-fabric trinity: registered lenders, service providers, methodology versions, and on-chain attestations by schema. Public read, no auth, no PII, no per-row data. Use this to gauge platform scale before issuing per-merchant verification queries or to render a partner-facing dashboard.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint), the description adds valuable behavioral context: 'Public read, no auth, no PII, no per-row data.' This clarifies the safety profile and data sensitivity, which is useful for an agent deciding when to call the tool and what to expect in responses.
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 two sentences long, with the main purpose front-loaded in the first sentence. The second sentence adds usage guidance and constraints without repetition or fluff. Every clause earns its place, making the description compact yet informative.
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?
Given the simple nature (no parameters, no output schema), the description fully covers what the tool does, what data it returns, and when to use it. It mentions public accessibility, absence of PII, and aggregate-only behavior. There are no obvious gaps for an agent to invoke this tool correctly.
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 tool has zero parameters, and the schema coverage is 100% (empty properties). The description adds meaning by explaining what is counted, but since there are no params, there is nothing to elaborate. The baseline of 4 for a no-parameter tool applies because the description compensates for the lack of parameter details by clarifying the output scope.
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 opens with 'Return aggregate-only counts of the droplinked trust-fabric trinity', clearly stating the verb (return), resource (trust-fabric stats), and scope (aggregate-only). It enumerates specific data categories (registered lenders, service providers, methodology versions, on-chain attestations by schema), which distinguishes it from sibling tools that perform per-merchant verification or return detailed records.
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?
The description provides explicit usage context: 'Use this to gauge platform scale before issuing per-merchant verification queries or to render a partner-facing dashboard.' It also states what it is not for ('no per-row data'), implying alternatives that provide per-merchant details. However, it does not explicitly name sibling tools as alternatives, so it stops short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as find_inventory, search_products, list_shop_products, and get_product all dealing with product discovery/retrieval with subtle differences. Similarly, verify_brand_attestation and get_brand_attestation_status could be confused, as could get_trust_dossier and get_underwriting_signals. The sheer number of verification and lookup tools makes it difficult to pick the right one without careful reading.
The cart tools use a dot-separated camelCase convention (cart.addLine, cart.updateLineQuantity), while the rest use snake_case with varied verbs (find_, get_, list_, search_, verify_, request_, quote_, etc.). This mixing of conventions and inconsistent verb choices (e.g., find_inventory vs search_products vs list_shop_products) makes the tool names unpredictable.
With 38 tools, this server is heavily overloaded. The guidance suggests 25+ tools is too many, and this server exceeds that threshold. While the domain spans commerce, trust attestations, and lending, the count is excessive for a coherent single-server toolkit.
The tool surface is extremely broad, covering cart management, checkout, product discovery, trust verification, and lending workflows. However, there are notable gaps: no cart retrieval or order history, no revoke/update for attestations, and some key lending tools (quote_credit_terms, report_repayment) are scaffolded but not yet functional, creating dead ends.
