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fit_text

Stop text overflow in PowerPoint: shrink overflowing text to fit its shape by estimating a uniform font scale, rewriting run sizes or applying normAutofit, and enabling autofit for one shape or the whole slide.

Instructions

Shrink overflowing text to fit: estimates the largest uniform font scale (floor min_size pt) via an average-glyph-width heuristic, rewrites explicit run sizes (or writes a normAutofit fontScale when sizes are inherited), and enables normAutofit. shape=None fits every overflowing text shape on the slide; one that cannot fit at min_size reports still_overflowing. An ESTIMATE (no font metrics): verify with export_slide_images (assembly-export pack). Saves atomically with two-slot backup; backup=False skips rotation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
shapeNo
slideYes
backupNo
min_sizeNo
file_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description carries the full transparency burden and does exceptionally well: it discloses the heuristic estimate, lack of font metrics, run-size rewriting logic, normAutofit enabling, still_overflowing outcome, atomic save, and backup rotation behavior. This gives an agent realistic expectations beyond a simple 'fit text' label.

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 front-loaded and free of filler. Each sentence contributes distinct information: core mechanism, shape=None behavior, estimation caveat, verification path, and save/backup semantics.

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 mutating tool with no annotations, this is unusually complete: it covers algorithm, scoping, failure reporting, verification, and persistence behavior. The remaining gaps are the undefined slide parameter and the lack of explicit sibling-tool comparisons, which keep it from a perfect score.

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 0%, so the description must compensate. It adds real meaning for shape, min_size, and backup, but the required slide parameter is never explained (type, format, or identifier), and file_path is only self-evident from its name. This leaves a meaningful invocation gap for at least one required parameter.

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 opens with a specific action ('Shrink overflowing text to fit') and names the resource it operates on (overflowing text shapes), with enough algorithmic detail to differentiate it from siblings like apply_edits or set_placeholder_text. The behavior is concrete and self-contained.

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?

It clearly implies the trigger condition (overflowing text), explains the all-shapes mode, and recommends export_slide_images for verification. It does not explicitly name a sibling alternative or state when not to use the tool, so it falls just short of full 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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