ai-agents-architect
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.
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npx tessl i github:duclm1x1/Dive-Ai --skill ai-agents-architect69
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Discovery
89%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a solid skill description with excellent trigger terms and completeness. The explicit 'Use when:' clause with natural keywords makes it easy for Claude to select appropriately. The main weakness is that the capability description uses category names rather than specific concrete actions, which slightly reduces specificity.
Suggestions
Replace abstract category names with concrete actions, e.g., 'Designs agent architectures, implements tool integrations, configures memory systems, and orchestrates multi-agent workflows' instead of 'Masters tool use, memory systems...'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (AI agents) and lists some capability areas ('tool use, memory systems, planning strategies, multi-agent orchestration') but uses abstract category names rather than concrete actions like 'implement', 'configure', or 'debug'. | 2 / 3 |
Completeness | Clearly answers both what ('designing and building autonomous AI agents, tool use, memory systems, planning strategies, multi-agent orchestration') and when (explicit 'Use when:' clause with trigger terms). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'build agent', 'AI agent', 'autonomous agent', 'tool use', 'function calling'. These are terms developers naturally use when seeking help with agent development. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche focused specifically on AI agent development with distinct triggers like 'autonomous agent', 'multi-agent orchestration', and 'function calling' that are unlikely to conflict with general coding or other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
35%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a reasonable conceptual overview of agent architecture patterns but fails to deliver actionable, executable guidance. The Sharp Edges table is incomplete with truncated solutions, and the patterns use pseudocode comments rather than real code examples. The content describes what to do rather than showing how to do it.
Suggestions
Complete the Sharp Edges table with actual code examples for each solution (e.g., show iteration limit implementation, complete tool spec example)
Replace pseudocode comments in patterns with executable code snippets showing real ReAct loop implementation
Add concrete validation checkpoints to workflows (e.g., 'Check iteration count before each action', 'Verify tool response schema')
Remove the first-person framing paragraphs and convert that space to actionable examples
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is relatively lean but includes some unnecessary framing ('I build AI systems...', 'I understand that agents fail...') and the patterns section uses pseudocode-style comments rather than executable code, adding tokens without proportional value. | 2 / 3 |
Actionability | The patterns are described abstractly with bullet points and comments rather than executable code. The Sharp Edges table references solutions but doesn't show them - entries like 'Always set limits:' are incomplete with no actual code or specific guidance. | 1 / 3 |
Workflow Clarity | The ReAct and Plan-and-Execute patterns outline sequences but lack validation checkpoints, error recovery steps, or concrete feedback loops. The mention of 'max iteration limits' is good but not shown concretely. | 2 / 3 |
Progressive Disclosure | The skill has reasonable section organization and references related skills, but lacks links to detailed documentation. The Sharp Edges table is incomplete (solutions cut off), and there are no references to deeper materials for complex topics like multi-agent orchestration. | 2 / 3 |
Total | 7 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Reviewed
Table of Contents
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