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extract_rent_roll

Read-only

Extract structured, verified data from a commercial real estate rent roll document (PDF, Excel .xlsx, or CSV; native or scanned). Returns property info, one record per unit (unit number, tenant, square feet, lease dates, rents, occupancy), stated totals, and a deterministic verification report that reconciles recomputed totals against the document's stated totals. Every field carries a status and confidence; uncertain fields are flagged, never silently guessed. Anonymous use is limited to 3 documents/day; pass an API key from rentrollapi.com via the X-Api-Key header for more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileNameYesOriginal file name including extension, e.g. 'rent-roll.pdf' — the extension guides format detection.
documentBase64YesThe rent roll document encoded as base64 (PDF, XLSX, or CSV bytes). Max 25 MB decoded.

TDQS

A4.2/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses extensive behavior: it returns a deterministic verification report reconciling recomputed totals against stated totals, flags uncertain fields with status/confidence, never guesses, and includes anonymous usage limits (3/day) plus API key authentication via X-Api-Key header. This is rich behavioral context that exceeds annotation coverage.

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 three sentences, front-loaded with the primary purpose, and every sentence earns its place: purpose and scope, output structure and verification behavior, and usage limits/authentication. No redundant or filler content.

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?

Given the absence of an output schema, the description provides a comprehensive overview of return values (property info, per-unit records, stated totals, verification report) and behavioral guarantees (status/confidence, flagging uncertain fields). It covers formats, limitations, and authentication. It does not enumerate every output field, but for a 2-parameter tool with no output schema, the description is remarkably complete.

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 description coverage is 100% for both parameters, and the schema already explains documentBase64 as base64-encoded PDF/XLSX/CSV bytes and fileName as the original name with extension guiding format detection. The description adds mention of scanned documents and size limits but does not meaningfully expand parameter semantics beyond the schema, so baseline 3 applies.

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 clearly states the tool extracts structured, verified data from a rent roll document, specifying the document types (PDF, Excel .xlsx, or CSV; native or scanned). This verb+resource combination is specific and distinguishes it from the sibling tool extract_operating_statement, which targets a different document type.

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 use for rent roll documents and contrasts with the sibling tool by naming the document type, but it does not explicitly state when to use this tool versus extract_operating_statement or provide exclusion criteria. The usage context is clear but not explicitly differentiated.

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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TDQS

A4.4/5.0
Disambiguation5/5

The two tools target distinct document types: one for T12/operating statements and one for rent rolls. There is no overlap in purpose; an agent can easily select the correct tool based on the document at hand.

Naming Consistency5/5

Both tool names follow a consistent 'extract_' prefix followed by the document type noun. The pattern is uniform and predictable, making it easy to infer the tool's function from its name.

Tool Count4/5

With only two tools, the server is minimal but well-scoped for its stated domain of extracting data from commercial real estate documents. It covers the two most common document types; a third tool might be plausible but the count is not excessive or insufficient for a focused utility.

Completeness4/5

The server covers the two core document types in commercial real estate analysis (T12/operating statement and rent roll). Minor gaps could include lease documents or property financial summaries, but for the apparent purpose, the surface is reasonably complete with no dead ends.