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.

Quality

56%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agent/skills/ai-agents-architect/SKILL.md

Quality

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.

The description has strong trigger terms and completeness with an explicit 'Use when' clause, making it easy for Claude to select appropriately. However, the specificity suffers from using abstract nouns ('memory systems', 'planning strategies') and self-promotional language ('Expert in', 'Masters') rather than concrete action verbs describing what the skill actually does.

Suggestions

Replace abstract claims ('Expert in', 'Masters') with concrete action verbs describing capabilities (e.g., 'Designs agent architectures, implements tool calling, builds memory systems, orchestrates multi-agent workflows')

Add specific deliverables or outputs the skill produces (e.g., 'Creates agent scaffolding, debugging workflows, prompt chains')

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 nouns rather than concrete actions. 'Masters' and 'Expert in' are vague claims rather than specific capabilities.	2 / 3
Completeness	Explicitly answers both what ('designing and building autonomous AI agents' with specific areas) and when (explicit 'Use when:' clause with trigger terms). The structure clearly separates capabilities from trigger conditions.	3 / 3
Trigger Term Quality	Includes natural keywords users would say: 'build agent', 'AI agent', 'autonomous agent', 'tool use', 'function calling'. These are terms users would 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'. Unlikely to conflict with general coding or other AI skills.	3 / 3
	Total	11 / 12 Passed

Implementation

22%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill functions as a sparse index page rather than actionable guidance. While it correctly uses progressive disclosure to link to sub-skills, the main content lacks any concrete instructions, code examples, or workflows. The role description and capability lists don't teach Claude anything it doesn't already know.

Suggestions

Add a quick-start section with a minimal executable agent example (e.g., a basic ReAct loop in 10-15 lines of code)

Include a decision tree or brief guidance on when to use each pattern (ReAct vs Plan-and-Execute)

Remove the 'I build...' role-play framing and capabilities list - replace with actionable content

Add a simple workflow: 'To build an agent: 1. Define tools → 2. Choose pattern → 3. Implement loop → 4. Add memory if needed'

Dimension	Reasoning	Score
Conciseness	The content is relatively brief but includes some unnecessary framing ('I build AI systems...', 'I understand that agents fail...') that doesn't add actionable value. The capabilities and requirements lists are somewhat redundant given the skill description.	2 / 3
Actionability	The skill provides no concrete code, commands, or executable guidance. It's entirely descriptive - listing capabilities and linking to sub-skills without any actual instructions on how to build agents.	1 / 3
Workflow Clarity	No workflow is defined. The content lists topics and links to sub-skills but provides no sequence, steps, or process for designing or building agents. No validation checkpoints or decision points are mentioned.	1 / 3
Progressive Disclosure	The structure attempts progressive disclosure by linking to sub-skills, which is good. However, the main skill provides almost no substantive overview content - it's essentially just a table of contents with no quick-start guidance or context for when to use which sub-skill.	2 / 3
	Total	6 / 12 Passed

Validation

90%

Warnings & errors only

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

Repository: Dokhacgiakhoa/antigravity-ide
Commit: 332e58b

Reviewed: 17 days ago

Table of Contents

Discovery Implementation Validation

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