How do I install the Verify Document skill?

Run npx skillmds@latest add sketchjar/verify-document-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Verify Document safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Verify Document?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Verify Document free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Verify Document?

Sketchjar (@sketchjar) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Verify Document by sketchjar — Agent Skill

Name: Verify Document
Rating: 4.5 (4 reviews)
Author: Sketchjar

Verify Document

Check whether a document (PDF or image) shows signs of tampering or forgery before you rely on it. Use when the user asks to verify a payslip, invoice, bank statement, ID document, contract, or any document where authenticity matters.

Sketchjar Updated Sep 22, 2026

File contents

Document Verification

Inspect a document for forensic authenticity signals — not a fraud verdict, but a risk band with the evidence behind it. Uses the Stipple API (free anonymous tier, no signup).

When to use

Before onboarding a tenant, contractor, or employee from uploaded documents
Before paying an invoice that arrived by email
Before relying on a bank statement, payslip, or certificate in any workflow
Reviewing documents in due diligence, claims processing, or loan applications

Instructions

Get the document. URL or local file path (PDF, PNG, JPEG, BMP, TIFF).
Optionally check the cache first. If the user has the file's SHA-256, check whether it's already been inspected (free):
```
curl "https://www.stipple.sh/v1/warrants/check?sha256=<hash>"
```
Run verification. POST the document:
```
curl -X POST https://www.stipple.sh/v1/warrants \
  -F "file=@payslip.pdf" \
  -H "Authorization: Bearer $STIPPLE_API_KEY"
```
Add ?fresh=true to force re-inspection of a previously cached document. Add ?deep=true for deep inspection (more thorough, more credits).
Interpret the response. Two independent axes — read both:

Axis Question it answers

risk_band Does anything look tampered? (low / medium / high)

inspection_quality Could the engine actually see enough to judge? (thorough / limited / poor)

A clean phone photo of a real payslip is commonly low risk + limited quality — low coverage is not risk. Per-signal evidence includes: amount/words mismatch, font discontinuity in values, date anomalies, document label integrity, identifier checksums (ABN/ACN/TFN), table arithmetic.
Report honestly. This is a signal with evidence, not a verdict:
- "risk_band: LOW — nothing looks tampered"
- "inspection_quality: limited — couldn't inspect everything; low coverage is NOT fraud"
- Show the per-signal evidence for anything flagged
Pair with related checks. For identity documents, follow with a 100-point identity check (/v1/identity-check). For extraction, use extract-document-data.

Axis	Question it answers
`risk_band`	Does anything look tampered? (low / medium / high)
`inspection_quality`	Could the engine actually see enough to judge? (thorough / limited / poor)

Output format

risk_band:           LOW — Nothing looks tampered.
inspection_quality:  limited
recommended action:  review_before_action

evidence (signals):
  [pass] Amount words/figure mismatch: Spelled-out amounts agree with figures.
  [pass] Font discontinuity in value: Numeric values share the font of surrounding text.
  [skip] Identifier checksum: No checksummable identifier (ABN/ACN/TFN) present.

Notes

Document types the engine recognizes (payslips, invoices, bank statements) get type-specific checks; unrecognized types get generic checks only — say so in your report
Identical files are cached by content hash — re-checking the same bytes returns instantly and free
This measures forensic integrity, not authorship style — for "was this written by AI", use AI-text detection instead
Anonymous free tier: shared weekly allowance. Free key at https://www.stipple.sh

---name: verify-document-2description: Check whether a document (PDF or image) shows signs of tampering or forgery before you rely on it. Use when the user asks to verify a payslip, invoice, bank statement, ID document, contract, or any document where authenticity matters.---# Document VerificationInspect a document for forensic authenticity signals — not a fraud verdict, but a risk band with the evidence behind it. Uses the Stipple API (free anonymous tier, no signup).## When to use- Before onboarding a tenant, contractor, or employee from uploaded documents- Before paying an invoice that arrived by email- Before relying on a bank statement, payslip, or certificate in any workflow- Reviewing documents in due diligence, claims processing, or loan applications## Instructions1. **Get the document.** URL or local file path (PDF, PNG, JPEG, BMP, TIFF).2. **Optionally check the cache first.** If the user has the file's SHA-256, check whether it's already been inspected (free): ```bash curl "https://www.stipple.sh/v1/warrants/check?sha256=<hash>" ```3. **Run verification.** POST the document: ```bash curl -X POST https://www.stipple.sh/v1/warrants \ -F "file=@payslip.pdf" \ -H "Authorization: Bearer $STIPPLE_API_KEY" ``` Add `?fresh=true` to force re-inspection of a previously cached document. Add `?deep=true` for deep inspection (more thorough, more credits).4. **Interpret the response.** Two independent axes — read both: | Axis | Question it answers | |---|---| | `risk_band` | Does anything look tampered? (low / medium / high) | | `inspection_quality` | Could the engine actually see enough to judge? (thorough / limited / poor) | A clean phone photo of a real payslip is commonly `low` risk + `limited` quality — **low coverage is not risk**. Per-signal `evidence` includes: amount/words mismatch, font discontinuity in values, date anomalies, document label integrity, identifier checksums (ABN/ACN/TFN), table arithmetic.5. **Report honestly.** This is a *signal with evidence*, not a verdict: - "risk_band: LOW — nothing looks tampered" - "inspection_quality: limited — couldn't inspect everything; low coverage is NOT fraud" - Show the per-signal evidence for anything flagged6. **Pair with related checks.** For identity documents, follow with a 100-point identity check (`/v1/identity-check`). For extraction, use `extract-document-data`.## Output format```risk_band: LOW — Nothing looks tampered.inspection_quality: limitedrecommended action: review_before_actionevidence (signals): [pass] Amount words/figure mismatch: Spelled-out amounts agree with figures. [pass] Font discontinuity in value: Numeric values share the font of surrounding text. [skip] Identifier checksum: No checksummable identifier (ABN/ACN/TFN) present.```## Notes- Document types the engine recognizes (payslips, invoices, bank statements) get type-specific checks; unrecognized types get generic checks only — say so in your report- Identical files are cached by content hash — re-checking the same bytes returns instantly and free- This measures *forensic integrity*, not *authorship style* — for "was this written by AI", use AI-text detection instead- Anonymous free tier: shared weekly allowance. Free key at https://www.stipple.sh

Frequently asked questions