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dataflow-mapping

Trace and document how data transforms through a multi-step pipeline or function chain, showing intermediate state at each step with concrete example values. Use when explaining a data pipeline or complicated codepaths, tracing how a value changes across function calls, answering questions like "how does X get to Y", or producing a step-by-step dataflow walkthrough for a code review or design doc.

99

1.15x
Quality

100%

Does it follow best practices?

Impact

98%

1.15x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

A focused, instruction-only skill that defines a concrete dataflow-trace format and demonstrates it with three concrete examples. It is concise, actionable, and well-organized with no external references needed.

DimensionReasoningScore

Conciseness

Lean body with no padding or explanations of concepts Claude already knows; the format spec and examples each earn their tokens. Could be tightened only marginally in the Tips section.

3 / 3

Actionability

Provides a concrete, copy-paste-ready output format plus three fully-worked examples with real values (records, owner_ids, SQL fragments), giving unambiguous guidance on what to produce.

3 / 3

Workflow Clarity

Single-purpose output task with an unambiguous format and a 'When to use which depth' section sequencing the approach; no destructive/batch operations require validation checkpoints, so the simple-skill allowance applies.

3 / 3

Progressive Disclosure

Well-organized into Format, depth guidance, Examples, and Tips with no external bundle files and no nested references; content fits cleanly in one overview file.

3 / 3

Total

12

/

12

Passed

Description

100%

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

A precise, third-person description that covers what the skill does, when to invoke it, and the concrete terms users would naturally say. It caps no dimension and avoids vague fluff.

DimensionReasoningScore

Specificity

Names multiple concrete actions — 'Trace and document how data transforms', 'showing intermediate state at each step with concrete example values' — rather than vague language.

3 / 3

Completeness

Explicitly answers what ('Trace and document how data transforms...showing intermediate state') and when via a clear 'Use when...' clause with several concrete triggers.

3 / 3

Trigger Term Quality

Natural phrasings a user would say appear directly: 'explaining a data pipeline', 'how does X get to Y', 'code review or design doc', 'tracing how a value changes across function calls'.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche — annotated dataflow tracing — with triggers (pipeline tracing, 'how does X get to Y') unlikely to fire for unrelated skills.

3 / 3

Total

12

/

12

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
gitlabhq/orbit-knowledge-graph
Reviewed

Table of Contents

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