ai-agent-development
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
39
37%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/antigravity-awesome-skills-claude/skills/ai-agent-development/SKILL.mdQuality
Discovery
54%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 identifies a clear niche with good framework-specific trigger terms (CrewAI, LangGraph) that make it distinctive. However, it lacks a 'Use when...' clause entirely, and the capability description stays at a high conceptual level rather than listing concrete actions the skill enables. Adding explicit trigger guidance and more specific actions would significantly improve selection accuracy.
Suggestions
Add a 'Use when...' clause with explicit triggers, e.g., 'Use when the user asks about building AI agents, setting up CrewAI crews, designing LangGraph workflows, or orchestrating multi-agent systems.'
List more specific concrete actions, e.g., 'Define agent roles and goals, configure agent tools, set up inter-agent communication, design state graphs, implement agent memory and planning loops.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (AI agent development) and mentions some actions/concepts like 'building autonomous agents, multi-agent systems, and agent orchestration,' but doesn't list specific concrete actions (e.g., 'define agent roles, configure tool usage, set up agent communication pipelines'). | 2 / 3 |
Completeness | Describes 'what' at a high level but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, a missing 'Use when...' clause caps completeness at 2, and the 'what' is also somewhat vague, bringing this to 1. | 1 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'AI agent', 'autonomous agents', 'multi-agent systems', 'agent orchestration', 'CrewAI', 'LangGraph', 'custom agents'. These cover both conceptual and framework-specific terms users would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | The combination of specific frameworks (CrewAI, LangGraph) and the focused domain of AI agent development/orchestration creates a clear niche that is unlikely to conflict with other skills. | 3 / 3 |
Total | 9 / 12 Passed |
Implementation
20%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is essentially a high-level table of contents that delegates all actual work to other skills via vague 'Use @skill-name' prompts. It provides no concrete, executable guidance—no code examples, no specific framework patterns, no actual implementation details for any of the seven phases. The repetitive template structure (Skills to Invoke → Actions → Copy-Paste Prompts) inflates token count without adding value.
Suggestions
Add at least one concrete, executable code example per major phase (e.g., a minimal CrewAI agent setup, a LangGraph state graph definition, a tool implementation pattern) instead of abstract action lists.
Replace the generic numbered action items ('Define agent purpose', 'Implement agent logic') with specific, actionable instructions that include framework-specific commands, configuration snippets, or decision criteria.
Add validation checkpoints with concrete verification steps (e.g., 'Run agent with test input X and verify output matches Y') rather than just a final checklist of vague quality gates.
Consolidate the repetitive phase structure—either make each phase substantive with real content, or compress the overview into a concise routing table that maps tasks to referenced skills.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose and repetitive. Each phase follows an identical template with vague action lists that add no real information. The 'Copy-Paste Prompts' are just 'Use @skill-name to do X' repeated seven times. The numbered action lists (e.g., 'Define agent purpose', 'Design agent capabilities') are generic platitudes Claude already knows. | 1 / 3 |
Actionability | No executable code, no concrete commands, no specific examples of agent implementations. Every phase consists of abstract action items like 'Choose agent framework' and 'Implement agent logic' without any actual guidance on how to do these things. The 'copy-paste prompts' are just skill invocation references, not actionable instructions. | 1 / 3 |
Workflow Clarity | The phases are clearly sequenced and logically ordered from design through evaluation, and there's a quality gates checklist. However, there are no validation checkpoints within phases, no feedback loops for error recovery, and no guidance on what to do when things fail. The workflow is more of a table of contents than an actionable process. | 2 / 3 |
Progressive Disclosure | The skill references many other skills (ai-agents-architect, crewai, langgraph, etc.) which suggests progressive disclosure, but no bundle files are provided to support these references. The SKILL.md itself is a monolithic repetitive structure that could benefit from being more concise at the top level with clearer navigation to the referenced skills. | 2 / 3 |
Total | 6 / 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 | |
- Repository
- sickn33/antigravity-awesome-skills
- Commit
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