lab-notebook skillA
lab-notebook is agent-read markdown (skill) from uchicago-dsi/ai-sci-skills: Record work in a lab notebook so it is both a literal activity log and an efficient re-entry aid. Use when the agent is running experiments, debugging workflows, triaging jobs, or updating project state that must be recoverable later..
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
# Lab Notebook ## Optimize For Re-entry And Auditability - A notebook should answer both: - what exactly happened? - what do we currently believe? - Prefer one low-friction chronological record plus a sparse current-summary layer. - Reuse the project's existing notebook pattern instead of inventing a new structure. ## Choose The Notebook Shape - If the project already uses one file with summary plus chronology, keep that shape. - If the project already uses a detailed campaign notebook plus a sparse top-level lab notebook, keep that split. - Do not create two equally detailed notebooks. - Default rule: - detailed layer: append literal work record - summary layer: update only when the decision or current understanding changes ## Use This Entry Contract For each meaningful experiment, debugging step, or job intervention, capture: 1. Question or goal. 2. Action taken. 3. Evidence: - commands, scripts, configs, paths, job IDs, artifacts, metrics. 4. Result: - what actually happened. 5. Conclusion: - the inference you are drawing, if any. 6. Inference confidence: - `low`, `medium`, or `high` when the entry is making a real inference. 7. Decision impact: …
Read the whole file at its exact version.
How to install
mdr add uchicago-dsi/ai-sci-skills/lab-notebook@git:20260921.9b3de7cmdr add uchicago-dsi/ai-sci-skills/lab-notebook@sha256:64d10d9bc98347bePin 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_sbf6h4d3uxtag3i3)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260921.9b3de7c latest | 2026-09-21 | 9b3de7c | 5,044 B | A | view · diff |
| git:20260320.999ac68 | 2026-03-20 | 999ac68 | 3,234 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5044 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
uchicago-dsi/ai-sci-skills · 20 stars · license MIT · pushed 2026-09-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_sbf6h4d3uxtag3i3 GET https://markdownregistry.com/api/v1/resolve?ref=uchicago-dsi/ai-sci-skills/lab-notebook GET https://markdownregistry.com/api/v1/blob/64d10d9bc98347be9c87ec7ad34f256850cb2cc93f95578af32b28513afb5584
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