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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.

71

1.40x
Quality

58%

Does it follow best practices?

Impact

91%

1.40x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./cli-tool/components/skills/ai-research/ai-agents-architect/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

47%Weight 40%Scale 1-5

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

A well-organized but hollow reference: it catalogues agent patterns and pitfalls concisely, yet delivers almost no executable guidance — pseudocode bullets, truncated solution stubs in the Sharp Edges table, and Anti-Patterns with zero explanation. Most critically, it offers no workflow for actually designing or building an agent, leaving the reader with vocabulary rather than a procedure.

Suggestions

Add a step-by-step design workflow (e.g. define task and success criteria → select control pattern → design tool registry with schemas → add iteration limits and error surfacing → set up tracing/evaluation), with an explicit validation checkpoint before deploying an agent.

Complete the Sharp Edges table's Solution column — every cell currently ends in a dangling colon ('Always set limits:', 'Implement tracing:') with no actual fix.

Give each Anti-Pattern a one-line explanation and concrete remedy, or cut them; replace the pseudocode pattern blocks with concrete, executable examples (real code or specific configuration), and delete the 'Requirements' section and first-person preamble, which restate what Claude already knows.

DimensionReasoningScore

Conciseness

The body is mostly lean lists, but contains unnecessary padding: the first-person preamble ('I build AI systems that can act autonomously... I balance autonomy with oversight') adds no instruction, and the 'Requirements' section ('LLM API usage', 'Understanding of function calling', 'Basic prompt engineering') explains concepts Claude already knows. Not anchor 2 because most of the body is tight pattern bullets; not anchor 4 because those two sections are pure trimmable fluff.

3 / 5

Actionability

The pattern sections give some concrete design guidance ('Include max iteration limits', 'Separate planner and executor models possible', 'Lazy loading for expensive tools'), but they are pseudocode bullet lists inside ```javascript fences, and the Sharp Edges table's Solution column is truncated stubs ('Always set limits:', 'Write complete tool specs:' with nothing after the colon). The Anti-Patterns are bare headers with no explanation or fixes. This matches anchor 3: some concrete guidance but incomplete, pseudocode instead of executable detail, missing key details.

3 / 5

Workflow Clarity

There is no sequence for the skill's actual task — how to design and build an agent end-to-end. The content is a catalog of patterns, anti-patterns, and pitfalls with no ordering, no decision guidance on when to pick ReAct vs Plan-and-Execute, and no validation or verification checkpoints anywhere. This fits anchor 2 (rough shape present, steps poorly defined, validation absent) better than anchor 3, which requires an actual listed step sequence.

2 / 5

Progressive Disclosure

The body is ~85 lines, cleanly sectioned (Capabilities, Requirements, Patterns, Anti-Patterns, Sharp Edges, Related Skills), with no nested or buried references — and no bundle files exist to check, so the skill is self-contained. Not anchor 5: the under-50-line simple-skill exception does not apply, and the Anti-Patterns/Sharp Edges sections contain stub content that either needs completing or belongs in a reference file.

4 / 5

Total

12

/

20

Passed

Description

70%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A solid description with an explicit 'Use when' trigger list and clear domain scoping, held back by buzzword-driven self-description ('Expert', 'Masters') instead of concrete capability statements. Trigger coverage is good but misses common synonyms like 'multi-agent' and 'agent framework'.

Suggestions

Replace persona claims ('Expert in...', 'Masters...') with concrete actions, e.g. 'Designs agent architectures, implements tool/function-calling loops, builds agent memory systems, and orchestrates multi-agent workflows.'

Add natural trigger synonyms to the 'Use when' clause, such as 'multi-agent system', 'agent framework', 'agent orchestration', and 'agent memory'.

Tighten the 'what' so it states what the skill does rather than what the persona knows, making the description clearly answer 'what' on its own.

DimensionReasoningScore

Specificity

Names the domain ('designing and building autonomous AI agents') and several sub-areas ('tool use, memory systems, planning strategies, and multi-agent orchestration'), but these are knowledge topics rather than concrete actions, and 'Expert in' / 'Masters' are self-descriptive buzzwords the guidelines penalize. It sits above anchor 2 (domain named, minimal actions) but does not reach anchor 4's list of specific concrete actions.

3 / 5

Completeness

Both parts are present: a 'what' ('designing and building autonomous AI agents... masters tool use, memory systems...') and an explicit 'when' clause with concrete triggers. Not anchor 5 because the 'what' leans on persona claims ('Expert', 'Masters') rather than plainly stating what the skill does.

4 / 5

Trigger Term Quality

'Use when: build agent, AI agent, autonomous agent, tool use, function calling' provides good natural-phrase coverage a user would actually say. Not anchor 5: common variations like 'multi-agent', 'agent framework', 'orchestration', or 'agent memory' are missing.

4 / 5

Distinctiveness Conflict Risk

The agent-design niche is mostly distinct, with 'build agent', 'autonomous agent' clearly scoping it away from the related skills it names. Minor overlap risk remains: 'tool use' and 'function calling' are generic LLM-API topics that could also trigger a prompt-engineer or API skill.

4 / 5

Total

15

/

20

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.

Validation — 15 / 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
davila7/claude-code-templates
Reviewed

Table of Contents

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