Databricks Field Guide by TechFabric

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Read-onlyIdempotent

Start using the Field Guide immediately. Call this for 'help me learn Databricks', 'try the Field Guide', or to begin certification prep. No arguments starts a Unity Catalog diagnostic. A topic opens its concept or chapter quiz; goal certification with an exam opens a covered domain's practice and flashcards, with official sources and honest gaps. An MCP Apps host opens the interactive card first; a terminal asks one question at a time. This is a learning companion, not a replacement for the Databricks development plugin. No sign-in, workspace access or saved personal data.

Input Schema

Name	Required	Description
`exam`	No	A certification id from exam_prep; implies certification. Defaults to data-engineer-associate.
`goal`	No	Learn by doing (default), or begin certification practice
`topic`	No	A concept or chapter; omit for a Unity Catalog diagnostic

Output Schema

Name	Required	Description
`sim`	No	The data the interactive view animates; its numbers are a model, said under assumptions, except the rates, which are the guide's
`try`	No
`exam`	No
`keep`	No	For an interactive view: what its Keep my progress button makes a resume code from (scope), and the reader's place when a resume code was sent (resumed). Holds no personal data; nothing is stored on the server.
`note`	No
`plan`	No	The guided plan: each domain, heaviest first, read, try the model, quiz; with the reader's progress (from done) and its next step
`step`	No	The plan step asked for, where the card opens
`asked`	No
`build`	Yes	The commit of the deploy that answered
`guide`	No	Guided mode for the view: steps, each a short title, one of the guide's points as its body, an optional tip, an illustrative scene and the section it cites; then a recap
`scope`	No
`score`	No	The reader's score, when they answered (answers, or the questions asked one at a time by elicitation); null otherwise
`title`	No
`total`	No
`ttlMs`	Yes	How long this answer may be kept before asking again, in milliseconds
`domain`	No
`chapter`	No
`concept`	No	The concept's id; null when none matched (see available)
`domains`	No
`related`	No
`summary`	No
`coverage`	No
`official`	No
`practice`	No	The domain's practice quiz, as quiz_me returns one
`sections`	No
`withheld`	No
`available`	No
`plan_step`	No	Opened from an exam plan: this step's place (n of total), the steps done with this one, the plan's next step, and back, the call that returns to the plan
`practices`	No	Each covered domain's practice quiz, by domain id, for the plan's quiz steps
`questions`	No
`what_next`	No	What to do after this concept, as calls: from a plan, its next step and back to it; a quiz on it; the next concept
`disclaimer`	No
`flashcards`	No	The domain's flashcards, as the flashcards tool returns them (structured content only)
`onboarding`	Yes
`assumptions`	No
`explanation`	No
`index_built`	Yes	When this deploy's index was built (ISO 8601)

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedOct 28, 2026

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 / plan_step

Added value: +{
+  "description": "Opened from an exam plan: this step's place (n of total), the steps done with this one, the plan's next step, and back, the call that returns to the plan",
+  "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"
+  ]
+}

addedOutput schema / properties / what_next

Added value: +{
+  "description": "What to do after this concept, as calls: from a plan, its next step and back to it; a quiz on it; the next concept",
+  "items": {
+    "properties": {
+      "call": {
+        "type": "object"
+      },
+      "id": {
+        "type": "string"
+      },
+      "label": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "id",
+      "label",
+      "call"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}

Changed1 schema field changedOct 26, 2026

addedOutput schema / properties / keep

Added value: +{
+  "description": "For an interactive view: what its Keep my progress button makes a resume code from (scope), and the reader's place when a resume code was sent (resumed). Holds no personal data; nothing is stored on the server.",
+  "properties": {
+    "kind": {
+      "type": "string"
+    },
+    "resumed": {
+      "type": [
+        "object",
+        "null"
+      ]
+    },
+    "scope": {
+      "type": "string"
+    },
+    "stale": {
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "kind",
+    "scope",
+    "resumed",
+    "stale"
+  ],
+  "type": [
+    "object",
+    "null"
+  ]
+}

AddedOct 26, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Annotations already cover read-only, idempotent, non-destructive and closed-world, and the description adds genuinely new facts: no sign-in, no workspace access, no saved personal data, plus host-dependent presentation (interactive card under an MCP Apps host vs. one question at a time in a terminal). That is behavioral context an agent cannot obtain from the structured fields.

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?

Information is front-loaded with the imperative and the trigger phrases, and every sentence carries routing or constraint value. It is dense — several ideas are compressed into each sentence — but nothing is redundant with the schema or annotations.

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?

An output schema exists so return values need no explanation; the description instead covers the variables that matter for correct invocation: mode selection from zero args, topic, or exam, host-dependent UX, and the absence of auth or setup requirements. Nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds routing semantics tying parameters together: no arguments means a Unity Catalog diagnostic, a topic opens its concept or chapter quiz, and goal=certification with an exam opens that domain's practice and flashcards. It also signals that exam implies certification, reinforcing the schema's own note.

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 clearly states this is an entry point to a Databricks learning Field Guide and enumerates what each mode starts (Unity Catalog diagnostic, concept or chapter quiz, certification practice with flashcards). It distinguishes itself from the Databricks development plugin, though it never names the closely related siblings (exam_prep, quiz_me, explore_concept, flashcards) it routes into.

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?

Explicit trigger phrases ('help me learn Databricks', 'try the Field Guide', certification prep) tell the agent exactly when to prefer this tool, and 'not a replacement for the Databricks development plugin' gives a when-not boundary. The guidance is strong but stops short of naming which sibling to call instead once inside a specific task.

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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