pdf-markdown-validator

A quality checker for converting PDF files into Markdown, a plain-text format commonly used for documentation. It measures whether tables, headings, bold text, and italic text survive the conversion accurately.

In plain words
What is it for?
Testing PDF extraction, comparing converters, tracking quality changes, enforcing quality checks in CI/CD pipelines, producing reports, finding recurring errors, and measuring processing performance.
Why use it?
It reveals when a PDF conversion looks complete but has lost important structure or formatting. Standard scores make it easier to compare conversion methods and detect regressions.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/raphaelmansuy/edgequake/pdf-markdown-validator
Any agent
npx skills add raphaelmansuy/edgequake --skill pdf-markdown-validator
Clone the repo
git clone --depth 1 https://github.com/raphaelmansuy/edgequake

Made for: Claude Code, Codex.

Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,922 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00041 $0.04922
Opus 5 $0.00020 $0.02461
Sonnet 5 $0.00008 $0.00984
Haiku 4.5 $0.00004 $0.00492

Measured 3d ago against content hash 0d235945095e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

pdf-markdown-validator scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/analyze_failures.py, scripts/batch_drift.py, scripts/compare_runs.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

sudo apt-get install -y pandoc
.github/skills/pdf-markdown-validator/SKILL.md · 725 lines

How it starts

The opening of the file, as written. The whole thing — 725 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF → Markdown Validator Skill

Validate PDF to Markdown conversion quality using a comprehensive, multi-dimensional evaluation framework. This skill provides standardized metrics, evaluation harnesses, and reporting tools to assess conversion fidelity across table accuracy, style preservation, robustness, and performance.

When to use

Use this skill when you need to:

  • Validate PDF extraction quality: Measure how accurately PDFs convert to Markdown
  • Compare conversion approaches: Benchmark different PDF processing implementations
  • Track quality improvements: Quantify gains from processing enhancements
  • Automate quality gates: Enforce minimum quality standards in CI/CD pipelines
  • Generate evaluation reports: Create detailed analysis of conversion successes and failures
  • Identify failure patterns: Discover systematic issues in specific PDF features
  • Measure performance regressions: Track processing speed alongside quality metrics

Core concepts

Validation Framework

The validation framework computes a composite quality score (0–100) combining four independent metric dimensions:

FinalScore = (0.40 × TableAccuracy) + (0.40 × StyleAccuracy)
           + (0.10 × Robustness) + (0.10 × Performance)

Each dimension is independent and can be evaluated separately or together.

1. Table Accuracy (40% weight)

Measures how accurately tables are detected and their cell content extracted.

Components:

  • Table Detection F1: IoU-based matching of predicted vs. gold tables (IoU ≥ 0.5 threshold)

    • Precision: correctly identified tables / all detected tables
    • Recall: correctly identified tables / all gold tables
    • F1: harmonic mean of precision and recall
  • Cell Content Accuracy: Token-level F1 averaging across matched table cells

    • Matches cells by position within detected tables
    • Unmatched cells score 0.0
    • Aggregates to mean F1 across all cells

Formula:

TableAccuracy = (0.5 × TableDetectionF1) + (0.5 × CellContentAccuracy)

Read the full file on GitHub · 725 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 725 lines · 41 tokens per session scan B 0d235945095e

Subscribe to this mod's changes

pdf-markdown-validator is a skill published in the GitHub repository raphaelmansuy/edgequake (2,080 stars, last pushed 3d ago), licensed Apache-2.0. It adds 41 tokens to every session and 4,922 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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