prompt-annotation

Annotate agent prompts with XML tags for gap detection and reuse analysis.

39|6|Updated Oct 8, 2025
One-click install
npx skills add https://github.com/lossyrob/phased-agent-workflow --skill prompt-annotation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-annotation
Source: https://github.com/lossyrob/phased-agent-workflow/tree/main/.github/skills/prompt-annotation
Command: npx skills add https://github.com/lossyrob/phased-agent-workflow --skill prompt-annotation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Annotates agent prompts with structural XML tags to enable comprehension, gap detection, and cross-project reuse.

Core Features & Use Cases

  • Tag-based prompt analysis: apply a consistent taxonomy to reveal prompt sections like agent identity, workflow, guardrails, and decisions.
  • Cross-project comparison: normalize prompts across agents to identify reusable vs workflow-bound content.
  • Gap detection and extraction: surface missing sections, extract structured artifacts for downstream tasks.

Quick Start

To annotate a sample agent prompt, provide the prompt text and let the tool wrap sections with the described tags, starting with > <agent-identity> and closing with </agent-identity>.

Frequently Asked Questions about prompt-annotation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I annotate agent prompts with structured XML tags?▼

To annotate agent prompts with structured XML tags, provide the prompt text and the tool wraps sections like agent identity and workflow with a defined tag taxonomy, starting with tags such as <agent-identity>.

What is XML tag-based prompt analysis for cross-project comparison?▼

XML tag-based prompt analysis applies a consistent taxonomy to reveal prompt sections like agent identity, workflow, and guardrails, enabling cross-project comparison by normalizing prompts to identify reusable versus workflow-bound content.

How do I detect missing sections and gaps in agent prompts?▼

To detect missing sections and gaps in agent prompts, apply structural XML annotation to surface absent sections and extract structured artifacts for downstream tasks.

Do I need a defined tag taxonomy to annotate prompts?▼

Yes, you need a defined tag taxonomy and a YAML frontmatter with name and description to execute the annotation pipeline that outputs structured metadata and visualizations.

Can I extract reusable patterns from prompts across multiple agents?▼

Yes, you can extract reusable patterns from prompts across multiple agents by normalizing prompt structures through XML annotation, which distinguishes reusable content from workflow-bound content.

What's the best way to structure prompt annotations for downstream tasks?▼

The best way to structure prompt annotations for downstream tasks is using an XML annotation pipeline with a defined tag taxonomy and YAML frontmatter, outputting structured metadata and visualizations.