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mrmaciej1

JustFill PDF Forms

by mrmaciej1

open_pdf

Detect fillable fields in PDFs and scanned images using saved templates, embedded AcroForms, or machine learning.

Instructions

Open a PDF (or a scanned image: jpg/png/tiff) and detect its fillable fields.

Images are converted to a single-page PDF automatically (deterministically, so a template saved for a photo matches the same photo next time).

Resolution order (best source wins):

  1. Saved template matching this exact file (deterministic, confidence 1.0)

  2. Embedded AcroForm fields (deterministic, confidence 1.0)

  3. ML detection (each field carries a confidence score)

force_detect=True skips steps 1-2 and re-runs ML detection from scratch — use it to rebuild a layout when the saved template is wrong or stale. min_confidence drops ML fields scored below it (templates/AcroForm are always kept). Returns a JSON summary + the field list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
max_pagesNo
force_detectNo
min_confidenceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, so description fully discloses traits: image conversion deterministic, resolution order, skipping steps with force_detect, and confidence handling. No contradictions.

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?

Well-structured with bullet points, front-loads purpose, every sentence adds value. Appropriately sized for the complexity.

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?

Highly complete given 4 params, no annotations, and output schema present. Only max_pages is not explained, but overall thorough.

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 0%, but description adds meaning for path, force_detect, and min_confidence. Missing explanation of max_pages parameter, which is a minor gap.

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 it opens a PDF or scanned image and detects fillable fields, listing three resolution methods. It distinguishes itself from sibling tools like fill_pdf or list_fields.

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?

Explicitly explains when to use force_detect, min_confidence, and the resolution order. Provides clear context for when to use this tool vs alternatives.

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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