Lists multiple specific concrete actions and domains: 'Write or audit AI agent system prompts component-by-component across identity, instruction architecture, behavioral constraints, tools, examples, context strategy, output format, and error handling.' This enumerates eight distinct components, making the capabilities very concrete.

Clearly answers both 'what' (write or audit AI agent system prompts component-by-component across eight named areas) and 'when' (explicit 'Use when...' clause listing eight specific trigger scenarios including designing, writing, reviewing, fixing, auditing, improving, tuning, and defining).

Includes a rich set of natural keywords users would say: 'system prompt', 'agent prompt', 'tool-use instructions', 'prompt structure', 'context strategy', 'output formats', 'error handling', 'multi-agent systems', 'design a new agent prompt', 'review an existing agent prompt'. These cover many natural variations of how users would phrase requests.

The niche is very specific — AI agent system prompt engineering — with distinct triggers like 'agent prompt', 'system prompt', 'tool-use instructions', 'prompt structure', and 'multi-agent systems'. This is unlikely to conflict with general coding, writing, or document skills.

The skill is lean and efficient throughout. It assumes Claude's competence with prompt engineering concepts, avoids explaining what system prompts or agents are, and uses compressed table format for the component pass. Every section earns its place with no padding or unnecessary exposition.

The skill provides highly concrete guidance: specific component anchors with exact phrasing patterns, constraint rewrite examples with before/after text, tool description templates, audit finding patterns with priority/section/risk/rewrite structure, and a complete mini output example showing the expected deliverable format.

The workflow is clearly sequenced (First Actions → Component Pass → Multi-agent check → Review → Delivery) with explicit validation at step 4 (every component addressed, output contract complete, gaps converted to assumptions). The expansion rule provides a clear decision framework for when to go deeper. The output contracts for both write and audit modes serve as checklists.

For a standalone skill with no bundle, the content is well-organized with clear sections that progressively build from workflow overview to component details to output contracts to patterns. The table format for the component pass keeps the overview scannable while the Patterns section provides deeper examples. No external references are needed given the skill's scope.