Analytics Legends — SAP Analytics Intelligence

One SAP end-customer profile (Legend tier)

get_sap_client_profile

Read-onlyIdempotent

The full profile of one SAP end-customer — SAP footprint (products in use, modules known), analytics solutions, identity and evidence fields. Requires a subscriber API key, Legend tier or above. id comes verbatim from find_sap_clients.rows[].id.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Profile id, verbatim from find_sap_clients.rows[].id.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`rows`	Yes
`tool`	Yes
`_meta`	No
`_attribution`	Yes
`result_count`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedJul 31, 2026
- removedOutput schema / properties / rows / items / properties / citation_note
```
Removed value: -{
-  "type": "string"
-}
```
- changedOutput schema / properties / rows / items / properties / id / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
- changedOutput schema / properties / rows / items / properties / name / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
AddedJul 31, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive, so the description adds value by disclosing the API key/tier requirement and the source of the id. It does not contradict annotations and provides meaningful operational context beyond the schema.

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?

Two compact sentences. The first states the purpose and content; the second covers auth and id provenance. No filler or repetition of annotations.

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?

For a simple single-parameter retrieval tool with an output schema present, the description covers purpose, content, auth, and id provenance. It is sufficiently complete to guide correct invocation without needing to explain return values.

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?

Schema already covers the only parameter with 100% coverage. The description adds extra semantic value by explicitly stating that `id` comes verbatim from find_sap_clients.rows[].id, reinforcing correctness of parameter use beyond the schema's brief label.

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 specifies a singular, concrete resource: the full profile of one SAP end-customer with listed content domains (SAP footprint, analytics, identity, evidence). It clearly distinguishes from the sibling find_sap_clients by referencing a specific id from that list.

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?

States the prerequisite (subscriber API key, Legend tier) and tells the agent that the id should come from find_sap_clients.rows[].id, implying the natural workflow: first list, then get detail. It does not explicitly mention when not to use alternatives, but the referential guidance provides sufficient usage direction.

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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