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spark-optimization

Apply spark optimization in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation.

Skill by sandbaseai

IndexedApache-2.0★ 201
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/sandbaseai-spark-optimization

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Apply spark optimization in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses spark optimization or its strengths fit the task.

Use cases: data, marketing, productivity

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/spark-optimization

What's inside

Skill name
spark-optimization
Description
Apply spark optimization in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses spark optimization or its strengths fit the task.
License
Apache-2.0
Instructions
43 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • sandbase-api-map.md · references/

SKILL.md (first lines)

# Spark Optimization

Use this Skill to produce a bounded, verifiable Spark Optimization outcome. Preserve the user's chosen stack, source material, and authorization boundaries.

Read [the SandBase API map](references/sandbase-api-map.md) only when the task genuinely needs an external data source or generative model.

## Workflow

1. Inspect the available files, runtime, versions, inputs, and existing conventions before deciding what to change.
2. Restate the requested outcome, constraints, acceptance checks, and any assumption that could change the result.
3. Produce the smallest complete implementation, analysis, or artifact that satisfies those checks.
4. Verify the real output with appropriate tests, previews, calculations, or source comparison; do not infer success from file creation alone.
5. Return the deliverable, evidence of validation, material assumptions, and unresolved limitations.

## Quality gates

- Inspect shapes, types, units, missing values, sampling, target leakage, and train/test boundaries before modeling or transformation.
- Pin or record relevant library versions, random seeds, parameters, and environment assumptions for reproducibility.
- Validate against a baseline or independent calculation and report diagnostics, uncertainty, failure modes, and resource use.

## Focus checks

- Inspect the physical plan and runtime metrics, size partitions deliberately, diagnose skew and shuffles, cache only reused data, and measure before and after under comparable conditions.

## SandBase boundary

Keep the core Spark Optimization work local. Use SandBase only for an explicitly requested external dataset or model inference step that is not part of the local analysis.

1. Call `sandbase_discover` with a short capability query.
2. Call `sandbase_inspect` for viable candidates and compare the live schema, coverage, limits, output, execution mode, and price.
3. Prefer a dedicated tool or API the user already has. Send only the minimum necessary data.
4. Before any paid call, show the endpoint, important arguments, current unit price, call count, and total estimate or uncertainty, then obtain confirmation.
5. Use `sandbase_account` before an approved multi-call batch and call `sandbase_run` only with current schema-defined arguments.
6. Poll asynchronous work with `sandbase_run_get` using the same run ID; never resubmit merely because it is pending.
7. Use `sandbase_runs` only to recover status or reconcile observed cost.

If SandBase is unavailable, continue with local work and authorized sources when possible. Do not silently switch providers, fabricate external results, or claim a generation or retrieval succeeded.

## Handoff

Provide the completed artifact or findings, concise reproduction steps, checks actually run, source or asset provenance, SandBase endpoint and run IDs when used, observed cost when available, and any follow-up that still requires user action.

From sandbaseai/sandbase-skills, Apache-2.0.

More from sandbaseai/sandbase-skills

Signals

Stars
201
Forks
21
Open issues
1
Last commit (this folder)
Sep 8, 2026 (1 month ago)
Last release
Aug 20, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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spark-optimization skill. Agent Mart. https://agentmart.dev/skills/sandbaseai-spark-optimization (last updated 2026-10-24)