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Portfolio import preview

portfolio_import_preview
Read-onlyIdempotent

Preview adding a book of companies to the caller team's monitored portfolio. Pass the book as CSV text whose header is identifier_type,identifier plus, optionally, name, currency, limit_amount and drawn_amount; at most 2,000 rows. Every row is matched by its registry identifier alone, where identifier_type is lei, uk_crn, de_register (register type, number and court, for example HRB 275806 München), us_cik or another national register scheme. The name column is echoed back and never used to match. Each row answers its outcome (add, reactivate, in_book, duplicate, ambiguous, unresolved, invalid), a reason, and the matched node_id and register name. Rows are paged with limit and offset in file order; counts and total always cover the whole file, so page on until offset reaches total. Nothing is written, and applying an import happens in the Stonewake dashboard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csvYesThe book as CSV text, header row first.
limitNoPage size, default 100, maximum 100.
offsetNoRows to skip, default 0.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/non-destructive annotations, the description explicitly states 'Nothing is written' and names the external place where the actual write occurs. It also reveals useful behavior: name is only echoed and never used to match, and paging counts are file-wide rather than page-scoped.

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 dense but well organized: purpose, input format, matching behavior, per-row output, paging, and side effects each get one clear clause. No sentence is filler or redundant with the schema.

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?

For a complex tool with no output schema, it lists the per-row outcome categories (add, reactivate, in_book, duplicate, ambiguous, unresolved, invalid), reason, matched node_id and register name, plus paging totals. The agent has what it needs to call the tool correctly and interpret the preview results.

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?

Although the schema already describes the three parameters, the description adds critical semantics for csv: header requirements, allowed identifier types with an example, the 2,000-row limit, and the meaning of the optional columns. It also enriches limit/offset with the file-order and whole-file-count semantics, which the schema does not mention.

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 description opens with a specific verb and object: 'Preview adding a book of companies to the caller team's monitored portfolio.' It distinguishes the tool from siblings by framing it as a preview rather than an applied mutation and closes by noting the actual import happens in the Stonewake dashboard.

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?

It specifies the exact input format (CSV text with required header and optional columns), the 2,000-row cap, how rows are matched, and the paging rule ('page on until offset reaches total'). It also gives an explicit when-not: nothing is written and applying happens in the dashboard.

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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