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Verify Library Integrity

verify_library_integrity
Read-onlyIdempotent

Verify data integrity of a library by checking hashes of all chunks to ensure 100% integrity.

Instructions

Verifies that all chunks in a library maintain 100% data integrity by checking hashes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
library_nameYesName of the library to verify

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
library_nameYes
total_chunksYes
verified_chunksYes
failed_chunksYes
integrity_percentageYes
all_verifiedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already pin the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), and the description adds behavioral context beyond them: the check is exhaustive ('all chunks') and hash-based, with a strict '100%' success criterion implying a hard pass/fail. It does not disclose potential cost of a full-library scan or failure-report behavior, but the output schema covers return details.

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 entire description is one front-loaded sentence of about 16 words: verb, resource, scope, and method, with zero filler. Nothing is repeated from the title or schema.

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 full annotations and an output schema, the description covers everything needed to call it: what it verifies, how, and how strictly. The only gap is usage context (when verification is warranted), which is a minor omission given the strong default clarity.

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% – library_name is already defined as 'Name of the library to verify' with a minLength constraint. The description's mention of 'a library' adds no parameter-level semantics beyond the schema, so the baseline of 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 names a specific verb ('verifies'), a specific resource ('all chunks in a library'), and a concrete method ('checking hashes'), which clearly distinguishes it from the sibling create/query/delete/search/stats tools. The '100% data integrity' scope makes its job unambiguous.

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?

Usage context is implied but not explicit: the hash-checking language signals a health-check/verification role, but the description never states when to run it (e.g., after ingestion or suspected corruption) or names alternatives. With get_library_stats as a sibling, explicit routing between a stats read and an integrity check would reduce ambiguity.

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