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Search WWDC + Apple docs

wwdc_search
Read-onlyIdempotent

Search WWDC sessions, Apple docs, tutorials, HIG, and Swift Evolution for ranked snippets covering APIs, deprecations, changes, and guidelines.

Instructions

Full-text + semantic search across WWDC sessions, Apple documentation, tutorials, HIG, and Swift Evolution. Returns ranked hits with snippets. When the local embedding model is available, hybrid FTS + vector reranking is used; otherwise search falls back to FTS only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoRestrict to a WWDC year.
kindsNo
limitNo
queryYesSearch query; supports multi-word phrases.
detailNoHow much judgment and context to include.standard
formatNoResponse formatmarkdown
offsetNo
topicsNoRequire WWDC session topics/status text to include every value.
judgmentNoInclude per-hit and overall search judgment metadata.
year_maxNoRestrict WWDC sessions to this year or older.
year_minNoRestrict WWDC sessions to this year or newer.
platformsNoRequire WWDC session platforms to include every value.
require_transcriptNoOnly return WWDC sessions with transcript text.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered. The description adds genuinely useful behavioral context beyond that: retrieval is hybrid FTS + vector reranking when the local embedding model is available, and silently degrades to FTS-only otherwise — a real runtime trait an agent should know.

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 tight sentences with the scope front-loaded, then the return shape, then the fallback behavior. No filler and every sentence carries 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?

For a read-only 13-parameter search with no output schema, the description covers what the tool does, the return form (ranked hits with snippets), and the retrieval-mode caveat. Parameter-level semantics are left to the 77%-covered schema, which is acceptable.

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 77%, so most parameters (year, kinds, limit, detail, format, topics, judgment, platforms, require_transcript) are documented in the schema itself. The description says nothing about any parameter, so it adds no meaning beyond the structured fields; baseline 3 applies.

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?

States a specific verb (search) and resource (WWDC sessions, Apple docs, tutorials, HIG, Swift Evolution) with the retrieval mode named. It is clear this is a broad multi-corpus search, though it never contrasts itself against the close sibling apple_search_all, leaving the agent to infer the boundary.

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 list of corpora implies the search scope, but there is no explicit when-to-use or when-not-to-use guidance and no alternative named (e.g., wwdc_transcript_search, apple_hig_search, wwdc_list_sessions). Usage is only implied.

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