scan-mechanicality
CommunityDiagnose prompt mechanicality at a glance.
Software Engineering#markdown#heuristics#evaluation#classification#diagnostic#ai-prompt#prompt-analysis
Authorfppfurtado
Version1.0.0
Installs0
System Documentation
What problem does it solve?
It helps determine whether a Markdown prompt blob is predominantly mechanizable (deterministic, rule-based) or heuristic-semantic (dependent on interpretation), enabling teams to decide where automation is feasible.
Core Features & Use Cases
- Automatic classification of a Markdown prompt into POSITIVO, AMBÍGUO, or NEGATIVO based on mechanical nature.
- Extraction of candidate substrings that map to deterministic rules, with objective justification from the text.
- Ignore prose and metadata to focus on substantive content for reliable assessment.
- Use Case: When auditing prompts across agent stubs, SKILL.md, or embedded prompts to identify where mechanization is viable.
Quick Start
Analyze the provided Markdown prompt and return a POSITIVO/AMBÍGUO/NEGATIVO classification with the identified mechanically actionable substrings and objective justifications.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: scan-mechanicality Download link: https://github.com/fppfurtado/pragmatic-dev-toolkit/archive/main.zip#scan-mechanicality Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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