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OptimistFi

get_company_brief

Read-only

The full multi-source SNAPSHOT of a company — one call that gathers every source and synthesises them. Reach for this when you want the whole picture of a company at once, or to compare several companies side by side (pass several entities).

Sector and industry, market cap and short interest, financials with growth and margin, price
and RSI, flow-based sentiment, recent insider trades and 8-K news, corporate actions, upcoming
catalysts, congressional activity, and the market backdrop.

This is the SLOW, heavy option: it fans out across many upstream sources and can take several
seconds. It is the wrong tool for a narrower question — those have instant, cached tools: the
standing investment case (whether the thesis holds together) is get_thesis; whether the
narrative matches the reported numbers is get_thesis with view="story"; how one specific figure
moves the case is get_thesis_impact; and one specific data type — prices, filings, ownership, an
analyst view, and so on — is that data type's own tool. The brief is for when all of it together
is actually wanted.

Assembling this snapshot from the individual tools takes eight calls and roughly 13,000 tokens;
this is about a tenth of that because lists are summarised rather than dumped. Reach for the
specific tools when you need full detail — history, every holding, a filing section.

since: an ISO date. Turns the brief from a snapshot into a WINDOW — event sections report only
what landed after that date, and price reports the move across it instead of the last close.
response_mode: "plain" gives a short beginner-friendly explanation, "raw" omits thesis
interpretation, and "standard"/"deep" preserve the complete current response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNo
entityNo
entitiesNo
with_marketNo
reading_levelNo
response_modeNostandard

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses that the call fans out across many upstream sources and can take several seconds, that lists are summarised rather than dumped (with token estimates), and that since/response_mode alter the output shape. These are behavioral traits the annotation alone cannot convey.

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 long but highly structured: purpose, contents, cost, routing guidance, and parameter semantics are each in their own block. The alternatives and parameter explanations earn their length for a complex tool; no filler or tautology.

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?

For a complex aggregator with six parameters and no output schema, the description covers purpose, contents, performance, exclusions, and key parameter behavior. It omits semantics for with_market/reading_level and does not describe the response envelope, but the listed sections and response_mode guidance largely fill the gap.

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?

With 0% schema description coverage, the description compensates for the key parameters: since is explained as converting the brief into a window and changing price reporting, and response_mode's four enum values are given concrete meanings. entity/entities are implied by the comparison use case, but with_market and reading_level receive no explanation, so compensation is incomplete.

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 opening line defines a specific verb and resource: a full multi-source snapshot of a company that gathers and synthesises every source. It also names sibling tools (get_thesis, get_thesis_impact, per-data-type tools) and explains the difference, so it is easily distinguished.

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?

Explicitly tells the agent when to reach for this tool (whole picture at once, side-by-side comparison) and when not to ('wrong tool for a narrower question'). Names alternatives for those cases and notes the heavy/slow cost, which is exactly the routing guidance an agent needs.

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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