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get_document_view

Read a Word document as anchored markdown with stable paragraph IDs, enabling low-token orientation and bulk editing. Anchors survive edits for stable addressability.

Instructions

Read the document as an anchored markdown projection, the low-token alternative to get_text for orientation and bulk editing. One block per paragraph, prefixed [hex] with a stable anchor id (from w14:paraId, which survives edits elsewhere in the document); headings carry # prefixes, tables render as pipe tables under [t:hex] with cells addressed t:hex:rNcN (1-based). Anchors work in every location object ({"anchor": "hex"}) and in apply_edits ops. scope: {"outline": "3.2"} for one heading's section, or {"paragraphs": {"start": N, "end": M}} (end exclusive); omit for the whole document. detail: "structure" (headings and counts only), "text" (default), "full" (adds {++ins++}/{--del--} revision markers and [cN] comment refs with an author legend). include: {"tables": false} to skip tables, {"notes": "inline"} to append footnote/endnote text. Documents without paraIds get VOLATILE anchors (flagged in the header) that change with any edit; stamp_anchors=true writes real paraIds so anchors become durable. Stamping is the ONE mutation this tool can make and runs only when explicitly requested, with the normal backup and validated save; plain reads never modify the file. A document open in Word is read from its last saved state. To locate a string, use find_text; to enumerate collections, use list_elements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNo
detailNotext
includeNo
file_pathYes
stamp_anchorsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv2.0.0

TDQS

A5/5.0
Behavior5/5

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

No annotations are provided, so the description must carry the full burden. It discloses the read-only nature, the single optional mutation via stamp_anchors, the volatile-anchor edge case, behavior when the document is open in Word, and the exact output representation. This is exceptionally transparent.

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 dense but every sentence adds necessary information: purpose, output format, anchor semantics, parameter explanations, safety behavior, and sibling routing. It is front-loaded with the core purpose and does not contain filler.

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 five parameters, no annotations, and a rich output behavior, the description covers all necessary operational context: anchor durability, mutation conditions, Word-open behavior, and alternative tool selection. It is sufficiently complete for correct tool invocation.

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

Parameters5/5

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

Schema description coverage is 0%, yet the description thoroughly explains all parameters: scope, detail, include, and stamp_anchors, with concrete examples and default behavior. It fully compensates for the absence of schema-level parameter documentation.

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 a specific verb and resource ('Read the document as an anchored markdown projection') and immediately differentiates it from get_text as the low-token alternative. It also explains the output format, so an agent can understand both what the tool does and how it is distinct.

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?

It explicitly says when to use this tool (orientation and bulk editing) and names the alternatives for other tasks: 'To locate a string, use find_text; to enumerate collections, use list_elements.' This gives clear routing guidance relative to siblings.

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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