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get_company_profile

Read-onlyIdempotent

Get Clarifo's analytical profile for a company: what it does, customers and distribution, geography, strategy, key risks (with materiality) and critical accounting policies. Use for qualitative context before drilling into numbers. The profile is LLM-generated from filings (source = "clarifo_analytical_profile"), not filing-grade data; for filing evidence use get_financial_statement / search_filing_content.

Args: company: Name or ticker, fuzzy-matched ("AAPL", "60 Degrees Pharma"). locale: "en" (default) or "fi"; an empty section falls back to the other locale. include_full_text: False (default) returns short previews per section; True returns the full narrative.

Returns company_name, updated_at, overview, products_services, customers, geography, strategy, risks, accounting (text + tags), structured, and sources (one company_profile card, evidence_strength="model_inference", linking to the profile page) with source_policy. With no profile yet: error plus alternatives naming the tools that serve the filing data.

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": {
      "company": "<company>"
    },
    "name": "get_company_profile"
  }
}

Input Schema

NameRequiredDescriptionDefault
localeNoen
companyYes
include_full_textNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld=false, so the bar is lower, yet the description still discloses the provenance and reliability caveat (LLM-generated, source='clarifo_analytical_profile', not filing-grade), the evidence_strength='model_inference' tag, locale fallback behavior, and the error-plus-alternatives failure path.

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?

Front-loaded with purpose then usage then args, so an agent gets the routing decision in the first two sentences. The Returns block enumerates every output field even though an output schema exists, which is redundant bulk in an otherwise tight definition.

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?

Complete for a three-param read tool: purpose, provenance caveat, param semantics, failure mode, and the source_policy/evidence_strength context are all present. Nothing an agent needs to call it correctly or interpret its trustworthiness is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

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 the load, and it does: company is fuzzy-matched with concrete examples ('AAPL', '60 Degrees Pharma'), locale documents en default and the empty-section fallback to the other locale, and include_full_text explains preview-vs-full-narrative with the False default.

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?

Names a specific verb and resource ('Get Clarifo's analytical profile for a company') and enumerates the sections returned (customers, geography, strategy, risks with materiality, accounting policies). It also states what the tool is not: filing-grade data, with the profiling distinction made explicit against get_financial_statement and search_filing_content.

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?

Gives an explicit when-to-use ('for qualitative context before drilling into numbers') plus named alternatives for the when-not case ('for filing evidence use get_financial_statement / search_filing_content'). The no-profile case even routes to 'alternatives naming the tools that serve the filing data.'

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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