cross-artifact-analysis

Perform cross-artifact consistency and coverage analysis across constitution, specification, plan, and task artifacts to detect gaps, conflicts, and misalignments before implementation.

509 stars

Best use case

cross-artifact-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Perform cross-artifact consistency and coverage analysis across constitution, specification, plan, and task artifacts to detect gaps, conflicts, and misalignments before implementation.

Teams using cross-artifact-analysis should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/cross-artifact-analysis/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/methodologies/spec-kit/skills/cross-artifact-analysis/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/cross-artifact-analysis/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How cross-artifact-analysis Compares

Feature / Agentcross-artifact-analysisStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Perform cross-artifact consistency and coverage analysis across constitution, specification, plan, and task artifacts to detect gaps, conflicts, and misalignments before implementation.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Cross-Artifact Analysis

## Overview

Analyze all pipeline artifacts (constitution, specification, plan, tasks) for consistency, coverage, and alignment. This is the pre-implementation quality gate that ensures all artifacts are coherent before code is written.

## When to Use

- After task decomposition, before implementation
- When verifying that all specification requirements have corresponding tasks
- When checking for contradictions between constitution and plan
- When assessing readiness for the implementation phase

## Key Principle

Every specification requirement must be traceable through the plan to at least one task. No artifact should contradict another. Coverage gaps and conflicts must be resolved before implementation.

## Process

1. **Build traceability matrix** - Map requirements -> plan components -> tasks
2. **Detect coverage gaps** - Requirements without corresponding tasks
3. **Identify conflicts** - Contradictory constraints or requirements across artifacts
4. **Verify constitution compliance** - Plan and tasks comply with governance
5. **Check acceptance criteria** - Task criteria match specification requirements
6. **Score consistency** - Numeric score (0-100) across dimensions
7. **Determine readiness** - Boolean assessment for implementation phase
8. **Human review** - Approve analysis results before proceeding

## Tool Use

Invoke via babysitter process: `methodologies/spec-kit/spec-kit-planning` (analysis phase)
Full pipeline: `methodologies/spec-kit/spec-kit-orchestrator`

Related Skills

heatmap-analysis

509
from a5c-ai/babysitter

Analyze user interaction heatmaps for attention patterns and click behavior

static-analysis-runner

509
from a5c-ai/babysitter

Run static analysis tools including SonarQube, ESLint, and multi-language linters

Static Analysis Tools Skill

509
from a5c-ai/babysitter

Integration with security-focused static analysis tools

Smart Contract Analysis Skill

509
from a5c-ai/babysitter

Ethereum and blockchain smart contract security analysis

Network Protocol Analysis Skill

509
from a5c-ai/babysitter

Network protocol capture, analysis, and fuzzing capabilities

Code Coverage Analysis

509
from a5c-ai/babysitter

Multi-language code coverage analysis, reporting, and quality gate enforcement

memlab-analysis

509
from a5c-ai/babysitter

Expert skill for JavaScript memory leak detection using Facebook MemLab. Configure MemLab scenarios, execute memory leak detection runs, analyze heap snapshots, identify detached DOM elements, find event listener leaks, and integrate with CI pipelines.

gpu-memory-analysis

509
from a5c-ai/babysitter

Specialized skill for GPU memory hierarchy analysis and optimization. Analyze memory access patterns, detect bank conflicts, optimize cache utilization, profile global memory bandwidth, and generate optimized memory access code patterns.

power-analysis

509
from a5c-ai/babysitter

FPGA power estimation and optimization skill for low-power design

cdc-analysis

509
from a5c-ai/babysitter

Specialized skill for clock domain crossing analysis and synchronizer design in FPGA designs

misra-c-analysis

509
from a5c-ai/babysitter

MISRA C compliance checking and static analysis integration

memory-analysis

509
from a5c-ai/babysitter

Embedded memory analysis, optimization, and leak detection