hub-equity-mcp

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get_silent_restatements

Read-onlyIdempotent

Detect silent restatements in financial filings where comparative figures change without an amendment, grouped by the filing that revealed them.

Instructions

Figures a later filing reprinted differently in its comparative columns, with no amendment filed, grouped by the filing that revealed them.

The restatements get_amendments cannot see: most restatements are never filed as a 10-K/A or an amended ESEF report. fiscal_year is the year of the restated figure. diff_pct is in percent.

Use for 'did X quietly change its past numbers?', 'restatements without an amendment', 'was FY2023 CapEx revised later?'.

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": {
      "entity_id": "<entity_id>"
    },
    "name": "get_silent_restatements"
  }
}

Input Schema

Name	Required	Description	Default
`entity_id`	Yes
`fiscal_year`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Oct 19, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive behavior, so the description does not need to restate safety. It adds useful semantic context: results are grouped by the revealing filing, no amendment is involved, and diff_pct is expressed in percent. It stops short of describing return-shape nuances or edge cases, but an output schema exists.

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 definition is front-loaded with the core behavior, then adds the key exclusion and field semantics, then closes with compact use cases. Every sentence contributes context and none is redundant.

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?

With annotations, an output schema, and only two parameters, the description covers the essential behavior and scope. The remaining gap is minor: entity_id and fiscal_year optionality are left to the schema rather than explained.

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 0%, so the description must carry parameter meaning. It explains fiscal_year as the year of the restated figure and mentions diff_pct, but it does not explain entity_id or clarify that fiscal_year is optional. Partial compensation for a two-parameter tool warrants a mid score.

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 states a specific operation: finding later-filed comparative figures reprinted without an amendment, grouped by revealing filing. It explicitly distinguishes itself from get_amendments by saying these are the restatements get_amendments cannot see.

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

Usage Guidelines5/5

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

It gives explicit use cases ('did X quietly change its past numbers?', 'restatements without an amendment') and names the relevant alternative, get_amendments, along with the condition that differentiates them. The when-to-use context is clear enough for an agent to route correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.