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Prepare for a Databricks certification

exam_prep
Read-onlyIdempotent

Interactive: certification prep for Databricks' exams (data-engineer-associate, data-engineer-professional, data-analyst-associate, machine-learning-associate, machine-learning-professional, genai-engineer-associate, context-engineer-associate, apache-spark-developer-associate): each domain with its weight as Databricks publishes it, the guide sections and concepts that bear on it, how much the guide covers it (said honestly, gaps included), the official exam page and guide, and practice questions from the guide's own text for one domain. Call it when the user says "help me prepare for the Data Engineer Associate" or "quiz me for the exam". Not affiliated with Databricks; no exam question is reproduced.

Input Schema

NameRequiredDescriptionDefault
doneNoThe plan steps the reader has done, by number or id (from an earlier result): progress lives with the reader, not the server
examNoThe exam: data-engineer-associate, data-engineer-professional, data-analyst-associate, machine-learning-associate, machine-learning-professional, genai-engineer-associate, context-engineer-associate, apache-spark-developer-associate. Omit it for the list.
stepNoThe plan step to open at (its id, as the step's call gives it)
domainNoOne of the exam's domains (its id, from the result), for its practice questions

Output Schema

NameRequiredDescriptionDefault
examYes
planNoThe guided plan: each domain, heaviest first, read, try the model, quiz; with the reader's progress (from done) and its next step
stepNoThe plan step asked for, where the card opens
askedYes
buildYesThe commit of the deploy that answered
titleYes
ttlMsYesHow long this answer may be kept before asking again, in milliseconds
domainYes
domainsYes
coverageYes
officialYes
practiceYesThe domain's practice quiz, as quiz_me returns one
availableYes
practicesNoEach covered domain's practice quiz, by domain id, for the plan's quiz steps
disclaimerYes
flashcardsNoThe domain's flashcards, as the flashcards tool returns them (structured content only)
index_builtYesWhen this deploy's index was built (ISO 8601)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / done
      Added value: +{
      +  "description": "The plan steps the reader has done, by number or id (from an earlier result): progress lives with the reader, not the server",
      +  "items": {
      +    "anyOf": [
      +      {
      +        "maxLength": 200,
      +        "type": "string"
      +      },
      +      {
      +        "type": "integer"
      +      }
      +    ]
      +  },
      +  "maxItems": 60,
      +  "type": "array"
      +}
    • addedInput schema / properties / step
      Added value: +{
      +  "description": "The plan step to open at (its id, as the step's call gives it)",
      +  "maxLength": 200,
      +  "type": "string"
      +}
    • addedOutput schema / properties / plan
      Added value: +{
      +  "description": "The guided plan: each domain, heaviest first, read, try the model, quiz; with the reader's progress (from done) and its next step",
      +  "type": [
      +    "object",
      +    "null"
      +  ]
      +}
    • addedOutput schema / properties / practices
      Added value: +{
      +  "description": "Each covered domain's practice quiz, by domain id, for the plan's quiz steps",
      +  "type": [
      +    "object",
      +    "null"
      +  ]
      +}
    • addedOutput schema / properties / step
      Added value: +{
      +  "description": "The plan step asked for, where the card opens",
      +  "type": [
      +    "string",
      +    "null"
      +  ]
      +}
  2. Changed1 schema field changed
    • changedInput schema / properties / exam / description
      Previous value: -"The exam: data-engineer-associate, data-engineer-professional, data-analyst-associate, machine-learning-associate. Omit it for the list."New value: +"The exam: data-engineer-associate, data-engineer-professional, data-analyst-associate, machine-learning-associate, machine-learning-professional, genai-engineer-associate, context-engineer-associate, apache-spark-developer-associate. Omit it for the list."
  3. Changed1 schema field changed
    • addedOutput schema / properties / flashcards
      Added value: +{
      +  "description": "The domain's flashcards, as the flashcards tool returns them (structured content only)",
      +  "type": [
      +    "object",
      +    "null"
      +  ]
      +}
  4. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, closed-world behavior, yet the description still adds real context: not affiliated with Databricks, no copyrighted exam questions reproduced, and coverage reported with gaps acknowledged. It doesn't describe the multi-call flow (list → domain → step) that governs behavior.

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

Conciseness3/5

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

The core intent is front-loaded, but it is delivered as one very long run-on sentence with a nested parenthetical that re-lists all eight exam slugs already covered by the schema. The trigger examples are useful; the duplicated slug inventory is not.

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?

With an output schema present and annotations covering safety, the remaining burden is the interaction model, which is mostly conveyed via the per-domain deliverable list and the disclaimers. It is only slightly short on how `step`, `done`, and `domain` compose across calls.

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 all four parameters are already documented, including `done` and `step`. The description adds only the omit-`exam`-for-list convention and that `domain` selects practice questions; it never mentions the `step`/`done` progression, so it stays at the baseline.

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 concrete resource (Databricks certification prep) and enumerates exactly what a call returns: per-domain weights, guide sections/concepts, coverage honesty, official links, and practice questions for one domain. It implicitly differentiates itself from quiz_me/flashcards by being the whole-exam prep surface, but never names a sibling explicitly.

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?

Gives verbatim user triggers ("help me prepare for the Data Engineer Associate", "quiz me for the exam") and notes that omitting `exam` returns the list, so the entry point is clear. It offers no exclusions, and the "quiz me" phrasing overlaps with the quiz_me sibling without routing guidance.

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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