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Builders in Fintech

Get an investor's follow-on scorecard

get_investor_scorecard
Read-onlyIdempotent

Follow-on scorecard for one investor by slug: of the portfolio companies it first backed at least the window ago, the share that raised a later approved round (equity or IPO) within the window, at least gap_days after entry. Only returned when the investor has at least min_eligible eligible companies. Arguments: slug (required). Unknown arguments are rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesInvestor slug from its URL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, closed-world behavior. The description adds the non-obvious conditional-return rule (requires min_eligible companies) and the exact eligibility criteria (first backed at least window ago, later round at least gap_days after entry), which is valuable context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core purpose, but then repeats 'Arguments: slug (required)' which is redundant with the schema, and the long eligibility clause is dense and could be split. It's not wasteful, but it's not maximally tight either.

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 single-parameter read-only tool with no output schema, the description covers the metric definition, eligibility conditions, and return condition. An agent has enough to call it correctly. Missing only alternate-tool routing, which is a minor gap.

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 coverage is 100%, so the schema fully documents the only parameter (slug). The description correctly identifies slug as required but adds no format or sourcing detail beyond the schema's 'Investor slug from its URL.' Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: 'Follow-on scorecard for one investor by slug.' The metric is precisely defined (share of portfolio companies that raised a later approved round within the window). It doesn't distinguish itself from siblings like most_active_investors directly, but the unique metric makes its purpose unmistakable.

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

Usage Guidelines3/5

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

The description implies when the tool returns data ('Only returned when the investor has at least min_eligible eligible companies') and mentions window/gap_days, but it never names an alternative tool or explicitly states when to use this versus most_active_investors or other investor tools. Usage context is implied, not guided.

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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