We collected the official blank PDFs for 137 government form entries (134 analyzed across 133 distinct PDF files, totaling 63.4 MB, 628 pages, and 19,512 terminal form fields) and ran a structural inspection using pypdf 6.6 to measure how government agencies actually construct and publish PDF forms.
The full dataset is available as a static, no-JS CSV under CC BY 4.0: – Direct CSV Download (137 rows × 26 columns): https://justfill.app/data/justfill-government-forms-fillability-2026-09-02.csv – Methodology, Caveats & Sortable Table: https://justfill.app/research/are-government-forms-fillable
Schema (26 Columns):
| Column | Type | Description |
|---|---|---|
slug |
string |
Canonical form identifier (e.g., w-9, i-129, fl-150, form-2848) |
formName |
string |
Official form number/title |
issuer |
string |
Full issuing agency name |
group |
string |
Agency cohort (IRS, USCIS, SSA, VA, State Dept, DOL, CMS, California courts, etc.) |
country |
string |
Jurisdiction (United States, United Kingdom, Germany, Spain, India) |
status |
enum |
ok (134), blocked (2 — HTTP 403 outside India), no_pdf (1 — online form only) |
pdfUrl |
string |
Direct agency URL fetched on collection date (2026-09-02) |
pages |
int |
Page count of the official blank PDF (total: 628, median: 3.0) |
sizeKb |
int |
File size in KB (largest: State Dept DS-64 at 3,150 KB) |
fields |
int |
Total terminal AcroForm input fields (excluding pushbuttons) |
textFields, checkboxes, radios, choices, signatures |
int |
Breakdown by widget type (14,207 text, 5,029 checkboxes, 202 dropdowns, 58 radio groups, 16 signatures) |
xfa |
bool |
Whether /AcroForm contains an /XFA XML package |
encrypted |
bool |
Whether the file carries owner encryption |
modifyDenied, annotateDenied |
bool |
Parsed PDF permission bits |
textLayer |
bool |
Whether page 1 yields >= 50 extractable characters |
producer, pdfVersion, edition |
string |
PDF producer metadata, version (1.5–1.7), and regex-extracted revision string |
namedFieldsShare |
float |
Share (0.0–1.0) of terminal field names containing a readable 4+ letter word token |
verdict |
enum |
xfa_hybrid (114), acroform (15), flat (5), xfa_dynamic (0), scanned (0) |
note |
string |
Collection anomalies (e.g., landing page 404 while PDF path remained live, empty /AcroForm dicts) |
Summary Statistics from the Snapshot:
- 85% (114 / 134) are
xfa_hybrid: 67/68 IRS forms, 24/26 USCIS forms, 10/13 California court forms, 4/4 SSA forms, and 5/5 VA forms include an Adobe/XFAlayer alongside AcroForm widgets. - 87% (116 / 134) were produced with Adobe LiveCycle Designer or Adobe Designer: Despite Adobe sunsetting LiveCycle years ago,
Designer 6.5andAdobe LiveCycle Designer ES 8.2 / 9.0 / 10.0dominate federal and state forms. - 49% (63 / 129) of fillable forms have opaque field names (
<10%readable): 61 of 68 IRS forms havenamedFieldsShare < 0.10(most are0.0, naming every fieldf1_1[0],f1_2[0], etc.), whereas USCIS, SSA, and VA use semantic camelCase names (LastName,ClaimantSSN). - 34% (45 / 134) carry owner encryption: All 45 permit form filling, 44 deny document modification (
modifyDenied), and 16 deny annotations (annotateDenied). - Outliers by field count: IRS
Form 709leads with 1,851 fields across 10 pages, followed by USCISForm I-129(980 fields, 38 pages), USCISForm I-485(760 fields, 24 pages), and IRSForm W-2(568 fields, 11 pages).
Bonus Dataset: Real-World AI PDF Field Detector Correction Telemetry
Alongside the structural government form study, we also published a reproducible 5-row PDF mail-merge benchmark fixture and real user correction logs (5,674 detected fields across 43 flat/scanned documents: 2.2% false-positive deletions, 1.2% missed-field additions, 3.5% geometry adjustments):
https://justfill.app/research/ai-pdf-form-filling-reliability
License: CC BY 4.0 (Attribution: JustFill, 2026-09-02). Feel free to use the CSV for visualizations, PDF parser testing, or civic-tech research!
submitted by /u/mcsno
[link] [comments]
