kata-agent-overview-design

Generate overview.md and system-prompt.md for operational agents.

Updated Sep 3, 2025
One-click install
npx skills add https://github.com/guardiatechnology/design-system --skill kata-agent-overview-design
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: kata-agent-overview-design
Source: https://github.com/guardiatechnology/design-system/tree/main/.claude/skills/kata-agent-overview-design
Command: npx skills add https://github.com/guardiatechnology/design-system --skill kata-agent-overview-design

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill produces an agent’s canonical identity documentation so teams can align on purpose, boundaries, stakeholders, and the exact operational instructions the agent must follow.

Core Features & Use Cases

  • Generate overview.md governance: Drafts the agent overview template including purpose, primary use case, out-of-scope, served features, ownership, origin, and value metrics.
  • Generate system-prompt.md instructions: Produces the consolidated system prompt containing the required four-block structure aligned to the lex-system-prompt specification.
  • Enforce reciprocity with served features: Validates that each listed feature exists and that each feature declares served_by_agents: [{agent}], and updates feature-agent mapping when needed.

Quick Start

Run the kata-agent-overview-design workflow with the target context, agent slug, tier, entry mode, owner, POV/source path (or ADR/PDR reference), served feature slugs, and PR reference to generate docs/{context}/agents/{agent}/overview.md and docs/{context}/agents/{agent}/system-prompt.md.

Frequently Asked Questions about kata-agent-overview-design

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

FAQPage Schema
How do I generate governance-grade agent identity documentation and a system prompt?

To generate governance-grade agent identity documentation and a system prompt, use a workflow that drafts overview.md and system-prompt.md by applying stepwise sourcing from PoV, DoOC, or ADR history, and validates reciprocity against feature docs.

What is reciprocity validation in agent design?

Reciprocity validation in agent design is the process of verifying that each served feature exists and declares served_by_agents, ensuring the agent overview aligns with feature-agent mapping before finalizing the system prompt.

How do I structure a system prompt using the lex-system-prompt specification?

Structuring a system prompt using the lex-system-prompt specification requires a consolidated four-block format, including a mandatory Block 1 stage declaration and OWASP LLM Top 10 2025 boundary guardrails integrated into Block 2.

Does agent overview generation work without existing ADR or DoOC sources?

Agent overview generation requires entry-mode-specific sourcing from PoV, DoOC, or ADR history, meaning you must provide a valid POV source path or ADR reference to produce the canonical overview.md and system-prompt.md outputs.

What is the best way to enforce boundary guardrails in an agent system prompt?

The best way to enforce boundary guardrails in an agent system prompt is to mandate inclusion of OWASP LLM Top 10 2025 security boundaries within Block 2 of the lex-system-prompt-aligned four-block structure during stepwise drafting.

Why does my agent overview fail reciprocity validation?

Agent overview reciprocity validation fails when listed served feature slugs do not exist in the documentation or when those feature docs lack the required served_by_agents mapping pointing back to the target agent.