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get_doc_smart_chips

Extracts all smart chips from a Google Doc, including person mentions and rich links, returning their type, location, and properties for auditing mentions or validating links.

Instructions

Extract every smart chip in a Google Doc — person mentions and rich links.

Walks the document body, finds all person and richLink inline elements, and returns their type, character range, and key properties. Useful for auditing @mentions (who is referenced where), validating links to external resources, or building a chip inventory before batch-editing. Does NOT include inline hyperlinks that never upgraded to chips (use a direct text scan for those).

Requires OAuth scope: https://www.googleapis.com/auth/documents.readonly (or broader). Read-only — safe to call repeatedly.

Scope note: This inspects the main document body only. Chips inside headers, footers, footnotes, or secondary tabs are not returned. Only chips that have been rendered/saved by the Docs client appear here — chips inserted programmatically via insert_doc_person_chip or insert_doc_file_chip won't show up in this result until a user opens the doc in the Docs UI and Docs upgrades the raw linked text into a chip.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_google_emailYes
document_idYesGoogle Docs document ID (from the URL after `/document/d/`).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: it walks the document body, finds person and richLink elements, returns type/character range/key properties, requires OAuth scope, is read-only, safe to call repeatedly, and explains limitations (no headers/footers, only rendered chips). No contradictions with annotations (none).

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?

The description is well-structured: it starts with a clear purpose, then details extracted elements, limitations, auth, and a scope note. Each sentence adds value without redundancy. It is appropriately sized for the tool's complexity.

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 presence of an output schema (implied), the description covers all necessary context: what is extracted, scope restrictions, auth requirements, and important notes about rendering. It is complete for an agent to decide when and how to use the tool.

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 coverage is 50% (only document_id has a description). The description does not add meaning for the user_google_email parameter beyond its name, which is fairly self-explanatory. However, the description adds value to the overall tool behavior, not the parameters. Given moderate coverage and clear parameter names, a score of 3 is appropriate.

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 states the verb 'extract' and the resource 'smart chips' with specific types (person mentions and rich links). It distinguishes from sibling tools like insert_doc_person_chip and insert_doc_file_chip by noting that programmatically inserted chips are not included, and contrasts with inline hyperlinks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly lists use cases (auditing @mentions, validating links, building chip inventory) and explicitly states what it does NOT include, providing alternatives (direct text scan for hyperlinks, user opening doc in UI for programmatic chips). This gives clear guidance on when to use this tool versus other methods.

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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