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Inarus

provgraf-mcp

by Inarus

list_facts

List a client's verified facts and documents from the provenance knowledge graph. Optionally filter by status to focus on confirmed, disputed, to_confirm, or resolved records.

Instructions

List the bank's facts and documents for a client.

client = owner slug (e.g. 'acme-housing'). status (optional) = confirmed|disputed|to_confirm|resolved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clientYes
statusNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. 'List' strongly implies a read-only, non-destructive operation initiated, and the client/status filter is disclosed. However, the description does not mention pagination, ordering, permissions, or any other behavioral guarantees, which keeps it at a moderate score.

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 compact and front-loaded: one clear sentence for the operation, followed by two concise parameter definitions. Every line serves a purpose, with no redundant filler or restatement of the tool name.

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?

For a simple list tool with only two parameters and an output schema, the description is largely complete: it identifies the resource, the required scoping, and the optional filter. It loses one point because it does not clarify when to choose this over sibling tools, but no return-value explanation is needed given 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%, and the description fully compensates by explaining 'client' as an owner slug with an example, and 'status' as an optional field with an explicit allowed-value list. This adds meaningful semantics that the input schema alone does not provide.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('List') and resource ('the bank's facts and documents') plus the client scoping, making the tool's core purpose clear. It does not explicitly differentiate itself from siblings like get_fact or search, so it loses one point, but the listing operation is distinct enough to be recognizable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the parameters but gives no guidance on when to use this tool versus get_fact, search, precedents, or check. There is no mention of when the list behavior is preferable, no exclusions, and no alternatives, so the agent must infer usage entirely from the tool's name and operation.

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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