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ravnlab

review-gate-mcp

by ravnlab

extract_with_gate

Extract specified fields from document text, automatically returning confident values and queuing uncertain ones for human verification.

Instructions

Extract fields from a document. High-confidence values return immediately; uncertain values are held in a human-review queue instead of guessed. Fields: invoice_number, total_amount, date, email, vendor_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe document text
fieldsYesField names to extract
Behavior4/5

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

Discloses the key behavioral trait of the gate (review queue for uncertain values) without annotations. Does not cover authentication or rate limits, but the core behavior is well explained.

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?

Three focused sentences: purpose, behavior, and field list. No redundant information.

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?

Adequate for a 2-parameter tool with no output schema. Explains extraction and gating. Could note what happens if all values are high-confidence or all uncertain, but overall sufficient.

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?

Schema coverage is 100% with basic descriptions. The description adds value by enumerating valid field names (invoice_number, total_amount, date, email, vendor_name), which is not in the schema.

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?

Clearly states it extracts fields from a document and lists the specific fields: invoice_number, total_amount, date, email, vendor_name. Distinguishes from siblings by explaining the gating behavior.

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?

Explains that high-confidence values return immediately and uncertain values go to a review queue, guiding when to expect immediate vs. deferred results. Does not explicitly state when not to use or mention alternatives, but siblings hint at post-extraction steps.

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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