IMPOCOR-AI Nexus

rag_quality_report

Read-only

Paid RAG evidence QA report. Purchase entitlement: https://ai.impocorgroup.com/agent-commerce/buy/rag-citation-freshness-qa

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "claims": "<claims>",
      "sources": "<sources>"
    },
    "name": "rag_quality_report"
  }
}

Input Schema

Name	Required	Description	Default
`claims`	Yes
`sources`	Yes
`entitlementSession`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 21, 2026

TDQS

C2/5.0

Behavior3/5

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

The description adds the important behavioral context that a purchase entitlement is required (via the purchase link), which is not captured in annotations. However, it provides no other behavioral details such as what consumes the inputs, side effects, or limits. Given readOnlyHint is present, the low burden is partially met, but more context (e.g., that it generates a report without modifying state) would be helpful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no filler. It states a purpose and includes a purchase link, both of which are relevant. However, it's overly terse and omits crucial details, but for conciseness as measured by word efficiency, it earns a high score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 3 parameters, no output schema, no additional annotations beyond readOnlyHint, and a complex domain (RAG QA). The description is drastically insufficient—it doesn't explain what the report contains, how it uses claims and sources, what the output looks like, or any constraints. This is far below what is needed for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description makes no reference to the 'claims' or 'sources' parameters, nor does it explain their purpose or format. With three parameters and zero elaboration, the agent cannot infer how to populate them correctly, making this dimension critically deficient.

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

Purpose2/5

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

The description 'Paid RAG evidence QA report' is a noun phrase that vaguely indicates the tool produces a report but lacks a clear verb and specific resource. It doesn't distinguish from sibling tools (e.g., inspect_rag_evidence) and is essentially restating the name with added context, making it ambiguous what the tool actually does.

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

Usage Guidelines1/5

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

No usage guidance is provided. The description only mentions that it's a paid report and includes a purchase link, but says nothing about when to use this tool versus alternatives, prerequisites, or typical scenarios. The lack of any 'when to use' or 'when not to use' information fails to guide the agent.

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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