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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.

95

1.15x
Quality

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

87%

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

The content is a well-structured, lean format specification with concrete worked examples and actionable guidance. Its main weakness is that the procedure for producing a trace is conveyed through examples rather than an explicit ordered workflow.

Suggestions

Add a short numbered 'How to produce a trace' procedure (e.g., 1. identify stages, 2. pick example values that expose edge cases, 3. annotate each stage, 4. verify input-to-output continuity) so the workflow is explicit rather than inferred from examples.

Consider a one-line self-check (e.g., 'confirm one piece of data is followable from input to output without re-reading source') to serve as a validation checkpoint for the produced trace.

DimensionReasoningScore

Conciseness

Lean body with no exposition of concepts Claude already knows; the format spec, three depth-differentiated examples, and tips each earn their place by demonstrating the exact annotation format the skill teaches.

3 / 3

Actionability

Provides a concrete copy-paste format template, three fully worked examples, explicit symbols (→ ✓ ✗ ←), and depth-selection guidance — giving specific, actionable instruction rather than vague direction.

3 / 3

Workflow Clarity

A sequenced format template and case-based depth guidance are present, but the actual procedure for producing a trace (identify stages → pick values → annotate → verify) is implicit rather than given as an ordered, checklisted workflow.

2 / 3

Progressive Disclosure

A single self-contained file organized into clearly headed sections (Format, When to use which depth, Examples, Tips) with no nested references; for this format-demonstration skill the inline examples are appropriately integral rather than bloating a separate file.

3 / 3

Total

11

/

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.

The description is specific, uses natural trigger phrasings, explicitly states both capability and use-when conditions in third person, and occupies a distinct niche. It is concise yet complete with no fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Trace and document how data transforms', 'showing intermediate state at each step with concrete example values' — rather than vague language, matching the anchor for multiple specific concrete actions.

3 / 3

Completeness

Explicitly answers both what ('Trace and document how data transforms...') and when via an explicit 'Use when...' clause enumerating triggering situations, so it is not capped at 2.

3 / 3

Trigger Term Quality

Covers natural terms users would actually say — 'data pipeline', 'complicated codepaths', 'how does X get to Y', 'dataflow walkthrough', 'code review', 'design doc' — giving good coverage of natural phrasings.

3 / 3

Distinctiveness Conflict Risk

It carves a clear niche (annotated dataflow tracing through pipeline/function chains) with distinct triggers unlikely to fire for unrelated skills; not generic enough to conflict broadly.

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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