Velarion Company Intelligence

Look up executive compensation

lookup_company_compensation

Read-onlyIdempotent

Look up executive compensation for a company in Velarion's coverage universe.

Returns CEO/NEO total compensation, pay mix breakdown, and canonical metrics for the requested fiscal year (latest available if omitted). Every figure comes from the company's own disclosure and carries its citation.

Out-of-coverage tickers return a structured error (not_in_coverage).

Input Schema

TableJSON Schema

Name	Required	Description
`ticker`	Yes	The company's ticker symbol (e.g. "AAPL").
`agent_token`	No	Optional Velarion agent token; falls back to the X-Velarion-Agent-Token header.
`fiscal_year`	No	Optional fiscal year to read (e.g. 2025). Defaults to the latest on file.

Output Schema

TableJSON Schema

Name	Required	Description
`error`	No
`ticker`	No
`p4p_gap`	No
`executives`	No	Named executive officers with SCT pay components.
`attribution`	No	Source citation, dataset DOI, and a ready-made cite_as string.
`fiscal_year`	No
`company_name`	No
`ceo_percentile`	No
`tsr_percentile`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 19, 2026

addedOutput schema / anyOf

Added value: +[
+  {
+    "required": [
+      "ticker"
+    ]
+  },
+  {
+    "required": [
+      "error"
+    ]
+  }
+]

removedOutput schema / required
```
Removed value: -[
-  "ticker"
-]
```

First observedSep 6, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive, and the description adds meaningful behavior beyond that: figures come from the company's own disclosure with citations, and out-of-coverage tickers produce a structured not_in_coverage error. This is useful operational context and does not contradict the annotations.

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 tightly structured: purpose first, return contents second, error behavior third. Every sentence earns its place, with no redundant or vague filler.

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?

Given the rich input schema, annotations, and output schema, the description covers the essential invocation concerns: what is returned, the default fiscal-year behavior, and the error case. The main missing piece is explicit routing among the compensation-related sibling tools, which is a selection concern rather than an invocation blocker.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description reiterates the fiscal-year default ('latest available if omitted') but adds no parameter-specific context beyond what the schema already documents. No additional semantics are needed, but none are contributed either.

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 names a specific verb and resource: 'Look up executive compensation for a company in Velarion's coverage universe,' and it spells out the returns (CEO/NEO total comp, pay mix, canonical metrics). It does not explicitly contrast with siblings like get_company_compensation or get_ceo_pay_ratio, so it stops short of full sibling differentiation.

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

Usage Guidelines3/5

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

The description implies use for looking up executive compensation within Velarion's coverage and gives an important boundary condition: out-of-coverage tickers return a structured error. However, it gives no explicit guidance on when to choose this tool over the compensation-related siblings or when not to use it.

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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