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Library id export — stable ids for the works homed here

get_library_ids
Read-only

Library id export — stable ids for the works homed here. Batch export of library_id rows (id, title, author, year, property tags) for the works that home on peopleanalyst.com. Ids are content-addressed (SHA-256 of normalized title|authors|year) and stable across repos, so a consumer can join to this catalog without string matching. Scoped to works homed here — titles whose canonical home is another property are excluded, matching /library.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoFilter by property tag, e.g. principia.
limitNoCap the number of rows returned.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
specYes
countYes
scopeYes
issuerYes
recordsYes
id_formatYes
generated_atYes
inventory_totalYes
excluded_foreign_homeYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful behavioral detail beyond that: IDs are SHA-256 of normalized title|authors|year, stable across repos, and the export excludes works whose canonical home is elsewhere. This helps an agent understand exactly what data is returned and how IDs are derived.

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

Conciseness4/5

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

The description is well-structured and informative, placing the core purpose first then adding id-derivation and scope details. There is minor redundancy with the title and the repeated 'works homed here' phrasing, but each sentence contributes useful content.

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?

Given the rich output schema, fully described parameters, and annotations covering safety, the description is complete. It clarifies the id-stability mechanism, the exclusion rule, and the join use case, leaving no significant gap for an agent to invoke it correctly.

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%, so the parameters tag and limit are already fully documented. The description adds no additional parameter-level guidance, which is acceptable given the schema's clarity, but it doesn't go beyond the baseline.

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 identifies the tool as a batch export of library_id rows for works homed on peopleanalyst.com, listing the exact fields (id, title, author, year, property tags). It also distinguishes itself by emphasizing content-addressed stable IDs, which separates it from generic catalog feeds and sibling tools.

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?

The description gives clear context: use this when you need stable content-addressed IDs to join to the catalog without string matching, and it explicitly scopes to works homed here, excluding titles whose canonical home is another property. It does not name specific sibling alternatives or state when-not-to-use explicitly, but the usage context is unambiguous.

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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