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 mikeOnBreeze/cc-crossbeam --skill adu-corrections-pdfgit clone --depth 1 https://github.com/mikeOnBreeze/cc-crossbeamWrote 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/mikeonbreeze/cc-crossbeam/adu-corrections-pdf)<a href="https://agentmods.dev/skills/mikeonbreeze/cc-crossbeam/adu-corrections-pdf"><img src="https://agentmods.dev/badge/skills/mikeonbreeze/cc-crossbeam/adu-corrections-pdf/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/mikeonbreeze/cc-crossbeam/adu-corrections-pdf"><img src="https://agentmods.dev/badge/skills/mikeonbreeze/cc-crossbeam/adu-corrections-pdf.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 | $0.00077 | $0.01459 |
| Opus 5 | $0.00039 | $0.00730 |
| Sonnet 5 | $0.00015 | $0.00292 |
| Haiku 4.5 | $0.00008 | $0.00146 |
Grade A, and why
adu-corrections-pdf 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 11d 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADU Corrections PDF Generator
Overview
Take a draft corrections letter in markdown and produce a professional PDF. This is a formatting-only sub-agent invoked by the research agent at the end of the pipeline.
Depends on: document-skills/pdf — the primitive PDF skill. Load it for the actual PDF generation tools (reportlab for Python, pdf-lib for JavaScript). This skill adds the domain-specific formatting on top.
What This Skill Does and Does NOT Do
| Does | Does NOT |
|---|---|
| Apply city letterhead styling | Research codes or review plans |
| Format sections, tables, confidence badges | Modify correction content |
| Generate paginated PDF | Make judgment calls about findings |
| Return screenshot for QA | Decide what goes in the letter |
Inputs
| Input | Format | Required |
|---|---|---|
| Draft corrections markdown | .md file path |
Yes |
| City name | String | Yes |
| Project address | String | Yes |
| Project info | Object: applicant, designer, engineer, scope, dates | Yes |
| Output path | File path for the .pdf |
Yes |
| Fix instructions | String (only on re-invocation after failed QA) | No |
Outputs
| Output | Format |
|---|---|
| Corrections letter PDF | .pdf at specified output path |
| QA screenshot | .png of page 1 — returned to calling agent |
Workflow
Step 1: Read Draft Markdown
Read the .md file. Validate expected structure: header block, notice, numbered sections, summary tables. Log warnings on unexpected structure but don't fail.
If fix_instructions are provided (re-invocation after failed QA), apply them before generating. Fix instructions might say: "Header is cut off — add more top margin" or "Table overflows page — reduce font size."
Step 2: Generate PDF
Use the document-skills/pdf primitive skill for the actual PDF generation. Two recommended approaches:
Approach A: reportlab (Python — best for structured layouts)
Use reportlab.platypus (SimpleDocTemplate, Paragraph, Table, Spacer, PageBreak) to build the letter programmatically. See document-skills/pdf/SKILL.md for reportlab patterns. This gives the most control over pagination, headers/footers, and table formatting.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 150 lines · 77 tokens per session scan A fed9317f137a
adu-corrections-pdf is a skill published in the GitHub repository mikeOnBreeze/cc-crossbeam (291 stars, last pushed 6mo ago), licensed MIT. It adds 77 tokens to every session and 1,459 once invoked, about $0.0004 per session on Opus 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 2026-08-30.
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