Skip to main content
Glama

Entity risk profile

entity_risk_profile
Read-onlyIdempotent

The caller team's credit-risk view of one company, by its graph node_id (the id search_companies hits carry). Answers one of three honest shapes: not in the portfolio (in_portfolio false), held but not yet assessed (assessment null), or the full current assessment with its status band, score, seen_share, explained_share and reachable_share (the figure the insufficient floor reads), a coverage_line of one to three sentences counting covered signals and gaps with their reasons, and every signal with its state (evidenced, register_quiet, gap, awaiting_bank_input, not_applicable), gap_reason, evidence grade (A to D), evidence value, note, and citation ids. A signal no connected source reaches for the company's jurisdiction is a gap, never not_applicable. A held company also carries entity_class: the class its checks route on (a bank is never scored on corporate distress models) and its source, either your team's analyst override or the register rule that derived it. A sole trader (sole_trader true, a natural person's business by its register's evidence) is never scored: assessment and entity_class are null. Company nodes only; person lookups answer not_found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_idYesThe graph node id, as returned by search_companies. Not the entity_id of company_profile.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / node_id / maximum
      Added value: +2147483647
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations by enumerating the three possible response shapes (not in portfolio, held-but-unassessed, full assessment), the signal state vocabulary, the jurisdiction gap rule, entity_class routing semantics, and the sole_trader null-scoring behavior. This is exactly the behavioral detail annotations cannot carry.

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 identifier are front-loaded in the first clause, and the dense tail earns its place by enumerating return values that have no output schema. However it is delivered as one long run-on paragraph, so heavy enumeration of states and grades is harder to scan than a structured list would be.

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?

With no output schema available, the description carries the full return-value burden and does so thoroughly: shapes, signal states, gap_reason, evidence grade A-D, citation ids, entity_class, and the sole_trader null case. An agent has everything needed to interpret results correctly.

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?

Single parameter with 100% schema coverage, so the schema already documents type and bounds; the description nonetheless adds real meaning by identifying it as the graph node id returned by search_companies and warning it is not company_profile's entity_id.

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?

States a specific verb+resource ('the caller team's credit-risk view of one company') and pins the identifier ('by its graph node_id'), explicitly contrasting it with company_profile's entity_id. An agent can distinguish it from search_companies, company_profile and company_financials without opening any schema.

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?

Gives a clear usage context (fetch the team's risk view for a known company node) and one concrete exclusion ('Company nodes only; person lookups answer not_found'), plus the routing hint that the id comes from search_companies. It stops short of naming an explicit alternative tool to call instead for held/assessed versus unheld cases.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources