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.
npx skills add roomi-fields/paper-trail --skill pdf-cascadegit clone --depth 1 https://github.com/roomi-fields/paper-trailWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/roomi-fields/paper-trail/pdf-cascade)<a href="https://agentmods.dev/skills/roomi-fields/paper-trail/pdf-cascade"><img src="https://agentmods.dev/badge/skills/roomi-fields/paper-trail/pdf-cascade/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/roomi-fields/paper-trail/pdf-cascade"><img src="https://agentmods.dev/badge/skills/roomi-fields/paper-trail/pdf-cascade.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00266 | $0.02037 |
| Opus 5.5 | $0.00106 | $0.00815 |
| Sonnet 5.5 | $0.00053 | $0.00407 |
| Haiku 4.5 | $0.00027 | $0.00204 |
Grade A, and why
pdf-cascade scanned grade A with 0 findings 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 1mo ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill : pdf-cascade
Purpose
Wraps the paper-trail worker B's acquisition cascade. Given a single
reference slug or a state filter, it advances the matching refs from
candidate toward page1_validated through the FSM, with strict page 1
anti-homonymy validation.
Anchors all downloads in the local registry (pdf_path, pdf_sha256,
acquisition_attempts[]) so the curator can audit everything.
When to invoke
Trigger this skill for any of:
- The user wants to fetch a PDF for a ref by slug
- The user wants to push the whole batch of
candidateoruid_resolvedrefs forward - The user explicitly calls
/paper-trail:cascade,/paper-trail:reactivate-ocr, or/paper-trail:status sota-writersub-task needs PDFs acquired for its proposed candidates
Do NOT invoke for semantic decisions (is this citation correct?) — that
belongs to sota-auditor.
How it works
The skill delegates to the worker B Python CLI:
# Single ref by slug
python -m pipeline run --ref <slug>
# Batch by state filter
python -m pipeline run --state candidate --limit 50
# Dry-run (no mutation)
python -m pipeline run --state candidate --dry-run
# Reactivate refs waiting for OCR
python -m pipeline reactivate-ocr
The CLI invokes the 8-source cascade (10 with
RESEARCH_ENABLE_SHADOW_LIBS=1 — see DISCLAIMER.md — and 11 when the
browser route is available too, see docs/ACQUISITION_HEADFUL.md). Each acquired
PDF must pass page 1 validation (author + title similarity ≥ 0.3 +
zero off-domain keywords) before being accepted into the registry.
Cascade order (default, without shadow libs)
1. Crossref OA (DOI-based, open-access metadata)
2. arXiv (preprints CS/math/physics/q-bio/q-fin/etc.)
3. OpenAlex (cross-domain academic graph)
4. Unpaywall (OA discovery, fallback)
5. HAL (Hyper Articles en Ligne, French academia)
6. CORE (UK-based open repository aggregator)
7. archive.org (digitized books and articles)
8. WebSearch queue (manual fallback — adds the ref to a queue for
human-driven search via Claude Code interactive)
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.
- 1mo ago First seen · 223 lines · 266 tokens per session scan A 39fc7ef6bd33
pdf-cascade is a skill published in the GitHub repository roomi-fields/paper-trail (6 stars, last pushed 1mo ago), licensed MIT. It adds 266 tokens to every session and 2,037 once invoked, about $0.0011 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
gemini-file-analysis
Analyze files (PDFs, images, audio, video, large source files) via Gemini's multi-modal file analysis. Use when a file is too large for Claude's context or when the file is a non-text format requiring visual/audio understanding.
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.
add-pdf-report
Internal implementation skill invoked by /add-native for app-generated PDF report workflows using expo-print and, when present, expo-sharing.
add-pdf-viewer
Internal implementation skill invoked by /add-native for native PDF control workflows. Handles HTTPS and file URI PDF viewing with @microsoft/power-apps-native-pdf-viewer 0.2.9+.
moai-docs-generation
Documentation generation patterns for technical specs, API docs, user guides, and knowledge bases using real tools like Sphinx, MkDocs, TypeDoc, and Nextra. Use when creating docs from code, building doc sites, or automating documentation workflows.
acmmm-camera-ready
Use when preparing the ACM MM (ACM Multimedia) camera-ready version of record — de-anonymizing safely, completing the ACM rights form and CCS concepts, meeting ACM sigconf requirements, releasing code/data/media artifacts and any earned reproducibility badge, registering, and planning the oral/poster presentation in…