Velarion Company Intelligence

Generate a governance alpha card

generate_governance_alpha_card

Read-onlyIdempotent

Generate a Governance Alpha Card for a company.

Composite deterministic card: pay alignment (Velarion's own P4P-style estimate, modeled on public peer-advisory methodology concepts — not licensed ISS data), governance scorecard, SoP risk band, peer quality, top risks/strengths. Requires the company to be in Velarion's coverage universe with current-period data.

This is the free sample of the $100 GOVERNANCE-ALPHA-CARD product. Each agent may draw a limited number of cards per UTC day; beyond that the tool returns free_tier_cap_reached together with the purchase path.

Structured errors returned (not raised) for:

not_in_coverage: ticker outside the covered universe
not_deliverable: the company's current-period disclosure does not support a card
free_tier_cap_reached: daily free allowance spent (buy it, or wait for 00:00 UTC)

Input Schema

TableJSON Schema

Name	Required	Description
`year`	No	Optional fiscal year to read (e.g. 2025). Defaults to the latest on file.
`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.

Output Schema

TableJSON Schema

Name	Required	Description
`error`	No
`status`	No	e.g. deliverable, free_tier_cap_reached.
`ticker`	No
`risk_band`	No
`attribution`	No	Source citation, dataset DOI, and a ready-made cite_as string.
`governance_scorecard`	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

A4.4/5.0

Behavior5/5

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

The description goes well beyond the annotations by disclosing that the card is deterministic, that structured errors are returned rather than raised, and by enumerating the specific error conditions: not_in_coverage, not_deliverable, and free_tier_cap_reached. It also explains the daily limit and purchase path, which is exactly the behavioral context an agent needs beyond the readOnly/idempotent hints.

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 well-structured and front-loaded, with the core purpose stated first, followed by component details and then error behavior. It is somewhat long, but every section earns its place given the tool's complexity and free-tier caveats.

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?

The description covers what the tool produces, prerequisites, failure modes, quota behavior, and product context. With an output schema present and full parameter documentation, nothing essential is missing for correct invocation.

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 input schema already documents ticker, year, and agent_token thoroughly. The description adds a little context about coverage and current-period data, but it does not need to repeat parameter-level semantics; the baseline of 3 is appropriate.

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 opens with a specific verb and resource: 'Generate a Governance Alpha Card for a company.' It then enumerates the card's components (pay alignment, governance scorecard, risk band, etc.), making the tool's deliverable explicit and clearly distinguishing it from sibling data-retrieval tools like get_company_compensation or get_say_on_pay_history.

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 provides clear usage context: the tool requires the company to be in Velarion's coverage universe with current-period data, and it is the free sample of a paid product with a daily per-agent cap. It does not name a specific alternative tool to use instead, but it gives enough conditional context for an agent to decide when this tool is appropriate.

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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