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jupyter-notebooks

Create, edit, or validate reproducible SQL or Python notebooks. Use for notebooks, SQL/Python scratchpads, reproducible exploration, audit trails, or runnable companions where the analysis should be reviewable or rerunnable.

66

Quality

78%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./packages/opencode/src/skill/builtin/.bundle/data-analytics/workflows/jupyter-notebooks/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

73%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a well-structured, actionable guide with a clear sequenced workflow, validation checkpoints, and a checklist. Its main weakness is conciseness, where the Standards section overlaps the workflow and some prose could be tightened.

Suggestions

Trim the Standards subsections that restate workflow steps (e.g., Notebook Structure and Reproducibility overlap steps 3-7) to reduce token cost without losing guidance.

Add one short, copy-paste nbformat/nbclient snippet for programmatically creating or executing a cell, since the only code present is the two bash commands.

Consider moving the detailed per-mode section templates or the data-source connector guidance into a reference file so SKILL.md stays a lean overview.

DimensionReasoningScore

Conciseness

The body is mostly efficient instructional prose without explaining basic concepts, but the Standards section restates workflow points and several paragraphs could be tightened, fitting the "mostly efficient but includes some unnecessary explanation" anchor rather than a 4.

3 / 5

Actionability

It gives concrete, executable commands (the nbconvert execute command and the uv pip install line), names specific tooling (nbformat, nbclient, JupyterLab), and provides concrete section templates, though much of the guidance is prose rather than copy-paste notebook code, leaving minor gaps.

4 / 5

Workflow Clarity

The 8-step workflow is clearly sequenced with explicit validation steps (steps 7 and 8), an execution feedback path for gaps, and a dedicated Validation Checklist, matching the anchor for clear sequence with checkpoints and checklists.

5 / 5

Progressive Disclosure

The content is well-organized into Workflow and Standards sections with clear headers and no nested references, and no bundle files exist to mismanage, but at ~120 lines some Standards detail could be trimmed or externalized, so it is good structure with minor gaps rather than a 5.

4 / 5

Total

16

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description clearly states both capabilities and use-when triggers in third person with good keyword coverage and a distinct notebook niche. It could reach the top band by adding more specific action verbs and the "Jupyter"/".ipynb" terms users naturally say.

Suggestions

Add the natural term "Jupyter" and the ".ipynb" file extension to the trigger list so users searching by those exact words land on this skill.

Sharpen the action verbs beyond the generic create/edit/validate (e.g., "execute notebooks top-to-bottom", "structure cells for reproducibility") to lift specificity into the top band.

DimensionReasoningScore

Specificity

"Create, edit, or validate reproducible SQL or Python notebooks" lists several concrete actions (create, edit, validate) tied to a named domain, but the verbs are somewhat generic compared to the highly specific actions in the anchor-5 example, so it sits at 4 rather than 5.

4 / 5

Completeness

It explicitly answers both what ("Create, edit, or validate reproducible SQL or Python notebooks") and when ("Use for notebooks, SQL/Python scratchpads, reproducible exploration, audit trails, or runnable companions...") with concrete trigger phrases, matching the anchor-5 example.

5 / 5

Trigger Term Quality

It surfaces natural terms like "notebooks", "SQL/Python scratchpads", "reproducible exploration", "audit trails", and "runnable companions", giving good synonym coverage, but it omits common variations such as "Jupyter" and the ".ipynb" extension, keeping it below a 5.

4 / 5

Distinctiveness Conflict Risk

The notebook framing is a clear niche with distinct triggers, but "SQL/Python scratchpads" and exploration language create minor overlap risk with general data-analysis or validation skills, so it is mostly distinct rather than minimal-conflict.

4 / 5

Total

17

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
XiaomiMiMo/MiMo-Code
Reviewed

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