paperlab-exam-alignment skillC
paperlab-exam-alignment is agent-read markdown (skill) from equinor/neqsim.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Skill: PaperLab Exam Alignment ## Purpose Check whether a PaperLab course book prepares students for the associated exercises and exams. Use this when a book has source folders with exams, exercise PDFs, review chapters, learning objectives, or end-of-chapter questions. ## Inputs - `source_manifest.json` or a source root containing `exams/` and `exercises/`. - Chapter markdown files with learning objectives and exercise sections. - Review/exam-preparation chapters. - Optional extracted exam text from `paperlab-source-pdf-to-html` or OCR. ## Workflow 1. Run `book-source-inventory` for source traceability. 2. Run `python paperflow.py book-exam-alignment <book_dir>`. 3. Review `exam_alignment.md` for topics marked `needs-review`. 4. For each weak topic, add a worked example, a self-test prompt, or a Chapter 26 review item. 5. If exam PDF text is available, rerun with extracted text and update the topic matrix with evidence from actual problem statements. ## Output - `exam_alignment.json` - `exam_alignment.md` ## Topic Matrix At minimum, map: - field-development framing, - PVT and flow performance, - processing and separation, - subsea, wells, and SURF, …
Read the whole file at its exact version.
How to install
mdr add equinor/neqsim/paperlab-exam-alignment@git:20260919.77c34a0mdr add equinor/neqsim/paperlab-exam-alignment@sha256:078c8614cb0edf42Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_uafjxxtb5x2tmwec)
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Versions
Audit of the latest version
- fail: Frontmatter block present
- fail: Frontmatter declares a name
- fail: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (1641 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
equinor/neqsim · 155 stars · license Apache-2.0 · pushed 2026-09-24 · branch master
API
GET https://markdownregistry.com/api/v1/artifacts/art_uafjxxtb5x2tmwec GET https://markdownregistry.com/api/v1/resolve?ref=equinor/neqsim/paperlab-exam-alignment GET https://markdownregistry.com/api/v1/blob/078c8614cb0edf422f609e36d2389ab036a15d4d2c1bf98fb14a445c48369f1a
Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.