Velarion Company Intelligence

Compare companies on pay, performance, governance

compare_companies

Read-onlyIdempotent

Compare multiple companies on pay, performance, and governance metrics.

Returns a ranked table drawn from disclosed compensation, performance, and governance data. The summary describes observed patterns in the returned data only. Out-of-coverage tickers are excluded (listed separately). Max 20 tickers.

Input Schema

TableJSON Schema

Name	Required	Description
`tickers`	Yes	List of ticker symbols to compare (e.g. ["AAPL", "MSFT"]), max 20.
`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
`tickers`	No
`attribution`	No	Source citation, dataset DOI, and a ready-made cite_as string.
`comparisons`	No	Ranked pay/performance/governance table.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 19, 2026

addedOutput schema / anyOf

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

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

First observedSep 6, 2026

TDQS

A4.3/5.0

Behavior5/5

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

The description adds meaningful behavioral context beyond the annotations: it clarifies that the returned table is based on disclosed data, that the summary only describes patterns in the returned data, and that out-of-coverage tickers are excluded but listed separately. These caveats help prevent an agent from over-generalizing results or silently dropping tickers, which is strong transparency for a read-only, idempotent tool.

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 four short sentences with no filler. The opening sentence states the core purpose, the second clarifies the output nature, the third prevents over-interpretation of the summary, and the fourth discloses coverage limits and handling. Every sentence earns its place.

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?

Given that an output schema exists, annotations cover the safety profile, and the description explains the tool's multi-company scope, ranking output, coverage behavior, and summary limitation, the definition provides everything an agent needs to select and invoke the tool correctly.

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 adds little parameter-specific meaning beyond repeating the 'max 20 tickers' constraint already present in the schema, so it does not exceed the baseline.

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 clearly identifies the action ('Compare multiple companies') and the resource domain ('pay, performance, and governance metrics'), and specifies the output as a ranked table. However, it does not explicitly differentiate this tool from closely related siblings such as benchmark_executive_pay, which may also involve comparison, so it falls short of full sibling-level distinction.

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?

The description makes the primary use case explicit: comparing multiple companies on relevant metrics, with a hard limit of 20 tickers and a stated behavior for out-of-coverage tickers. It does not explicitly mention when not to use this tool or name a preferred alternative, so it earns a 4 rather than a 5.

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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