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ai-agent-development

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

62

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The skill is token-efficient and well-structured across seven sequenced phases, but guidance is mostly abstract — phase actions describe rather than instruct, and no per-phase validation checkpoints exist. The single-file body has no progressive-disclosure reference structure.

Suggestions

Replace abstract Actions ('Define agent purpose', 'Implement agent logic') with concrete, executable guidance — e.g. specific framework setup commands, minimal code templates, or exact configuration steps — to raise actionability.

Add explicit validation checkpoints between phases (e.g. 'Verify agent responds to tool calls before proceeding to orchestration') and feedback loops, since this is a multi-step build process.

Move per-phase detail into reference files under references/ and link them one level deep so the SKILL.md body becomes a lean overview, improving progressive disclosure.

DimensionReasoningScore

Conciseness

The body is lean and free of concept-explaining padding; each phase is a terse template (skills to invoke, five actions, one prompt) that assumes Claude's competence, with no explanations of what agents or frameworks are.

3 / 3

Actionability

The 'Copy-Paste Prompts' are concrete skill invocations ('Use @crewai to build multi-agent system with roles'), but the per-phase Actions lists are abstract directives ('Define agent purpose', 'Implement agent logic') with no executable code, commands, or specifics — incomplete guidance.

2 / 3

Workflow Clarity

The seven phases are clearly sequenced, but there are no validation checkpoints or feedback loops between phases; the only verification is a terminal Quality Gates checklist, leaving sequence present but checkpoints implicit.

2 / 3

Progressive Disclosure

Content is well-organized into clear sections but is a single monolithic file over 50 lines with no external reference structure; the 'Skills to Invoke' entries are skill invocations rather than bundle-file references.

2 / 3

Total

9

/

12

Passed

Description

82%

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 is specific and distinct, naming concrete capabilities and frameworks a user would naturally invoke. Its main weakness is the absence of an explicit 'Use when...' trigger clause, which caps completeness at 2.

Suggestions

Add an explicit trigger clause such as 'Use when building autonomous agents, multi-agent systems, or orchestrating agents with CrewAI or LangGraph.' to raise completeness to 3.

Consider adding a few natural variation terms (e.g. 'agent frameworks', 'agent orchestration') to broaden trigger coverage further.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities ('building autonomous agents, multi-agent systems, and agent orchestration') plus named frameworks ('CrewAI, LangGraph, and custom agents'), matching the anchor for multiple specific concrete actions.

3 / 3

Completeness

Clearly answers 'what' the skill does but lacks any explicit 'Use when...' trigger clause, so per the judging guidelines completeness is capped at 2 with 'when' only implied.

2 / 3

Trigger Term Quality

Contains natural terms a user would say ('autonomous agents', 'multi-agent systems', 'agent orchestration', 'CrewAI', 'LangGraph') giving good coverage of likely trigger phrases.

3 / 3

Distinctiveness Conflict Risk

The named frameworks (CrewAI, LangGraph) and focused 'AI agent development' niche make it clearly distinguishable and unlikely to trigger for the wrong skill.

3 / 3

Total

11

/

12

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
boisenoise/skills-collections
Reviewed

Table of Contents

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