FinancialMD

What FinancialMD covers (and does not)

coverage

Read-onlyIdempotent

Say whether FinancialMD serves a dataset, and if not, why and what to use instead. Call it before searching for data that may not be here: Street consensus estimates, EPS and revenue estimates, analyst ratings, price targets, earnings call transcripts and audio, real-time, intraday or consolidated prices, CUSIP or ISIN, Morningstar research, wire news, mutual fund NAV, logos, politician (congressional) trades, fund letters and model estimates are not served (licensed, not built, or waiting on a decision). With no topic it lists every dataset with its routes and tools. Metadata read: free. If a dataset, field, company or analysis you need is missing, call request_data.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "topic": "consensus estimates"
    },
    "name": "coverage"
  }
}

Input Schema

Name	Required	Description	Default
`topic`	No	What you are looking for, in a few words (for example "consensus estimates", "transcripts", "intraday prices", "segments").
`status`	No	Only datasets with this status.

Output Schema

Name	Required	Description
`data`	No	{ datasets: [{ id, name, status, routes, mcp_tools, reason, licence, alternatives }], note }
`meta`	No	Request metadata: request_id, as_of, company resolution, coverage, pipeline_version, licence, terms, proof_base.
`error`	No	Present only on isError results: the API error code and message plus remedy hints.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already establish read-only, idempotent, closed-world behavior, so the description's job is to add cost and side-channel context — it does, stating 'Metadata read: free' and explaining the no-topic enumeration mode. It does not discuss output shape or rate limits, but the existing output schema and annotations cover much of that.

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?

Purpose and call-timing are front-loaded, and the long not-served list is dense but functional because it prevents wasted lookups. The paragraph runs long and the 14-item enumeration could be tightened, but no sentence is filler.

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 an output schema exists and annotations cover safety, everything an agent needs is present: what the tool answers, when to call it, what happens with zero arguments, cost, and where to go when the answer is negative. Nothing material is missing for a two-optional-parameter metadata tool.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning the schema lacks: the effect of omitting 'topic' (full dataset listing with routes and tools), and the intent behind the status filter via 'licensed, not built, or waiting on a decision'. Only the exact enum mapping is left implicit.

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 first sentence gives a specific verb and resource: say whether FinancialMD serves a dataset, plus the fallback outputs (why not, and what to use instead). It is immediately distinguishable from siblings like screen or filing_search, which retrieve data rather than answer coverage questions.

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?

Explicit timing is given ('Call it before searching for data that may not be here'), explicit no-argument behavior is given ('With no topic it lists every dataset'), and the alternative is named ('call request_data' when something is missing). The negative list enumerates concrete query types so an agent can self-screen before invoking.

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

All FinancialMD tools Inspect

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