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Glama

Apple entity cross-references

apple_cross_references
Read-onlyIdempotent

Find which sessions mention an API, which proposals a session implements, or related sessions by retrieving edges from the Apple developer cross-reference graph.

Instructions

Returns outgoing and/or incoming edges from the cross-reference graph for a given entity. Use to find: which sessions mention an API, which proposals a session implements, which APIs a session covers, related sessions. Build the graph with npm run ingest -- --source cross-reference.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoResponse formatmarkdown
directionNo'out' = edges FROM this entity, 'in' = edges TO this entity, 'both' = all.both
entity_idYesEntity ID, e.g. 'wwdc2024-10016' for a session, 'swiftui/view' for a doc, 'SE-0428' for a proposal.
entity_typeYesType of the entity.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful non-annotation context: the graph must first be populated with `npm run ingest -- --source cross-reference`, which tells the agent why results could be empty. It stops short of describing pagination or edge metadata.

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?

Two sentences, both front-loaded: the first defines the operation and directionality, the second supplies use cases and the data prerequisite. No filler, no repetition of the title.

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 read-only graph query with no output schema and fully documented parameters, the description covers operation, directionality, use cases and a setup prerequisite. The main remaining gap is what an edge record actually contains (edge type/label), which the agent would have to discover at call time.

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%, including a clear enum gloss for `direction`, so the schema carries the parameter burden and baseline is 3. The phrase 'outgoing and/or incoming edges' loosely mirrors the `direction` parameter but adds no syntax or semantics beyond what the schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource: 'Returns outgoing and/or incoming edges from the cross-reference graph for a given entity', with concrete examples of what those edges represent. It is clear what the tool does, but it never differentiates itself from overlapping siblings such as wwdc_related_sessions or wwdc_sessions_for_api, which cover some of the same questions.

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?

It supplies concrete when-to-use scenarios ('which sessions mention an API', 'which proposals a session implements', 'related sessions'), which is stronger than implied usage. However, it names no exclusions or alternative tools, so the agent must infer when a sibling would be a better choice.

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