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agent-builder

Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration

60

Quality

71%

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tessl review fix ./skills/agent-builder/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%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.

The body is a well-organized overview that excels at progressive disclosure, pointing to real, categorized reference and script bundles. Its weakness is that it leans on design philosophy and pseudocode rather than concrete executable guidance in the body itself, with some motivational padding.

Suggestions

Replace or supplement the pseudocode loop with a minimal executable Python snippet (or a direct pointer to a runnable example earlier in the body) so Claude has copy-paste-ready guidance without opening a reference file.

Trim motivational restatements (e.g. repeated 'Trust the model' reframes and the 'Agent Mindset' From/To section) to reduce tokens that restate concepts Claude already knows.

Add a short 'start here' checklist that ties the design-thinking questions to the init_agent.py scaffolding step, giving a concrete first action for the common case.

DimensionReasoningScore

Conciseness

Mostly efficient but padded with motivational restatements ('The magic isn't in the code', 'Trust liberates', 'The best agent code is almost boring') and conceptual explanations of agent fundamentals Claude already knows, fitting 'mostly efficient but includes some unnecessary explanation'; not 4 because the philosophy reframes are non-essential, not 2 because it is not severely verbose.

3 / 5

Actionability

Provides a pseudocode agent loop and design tables rather than executable code, with real executable guidance delegated to referenced bundle files, matching 'some concrete guidance but incomplete; pseudocode instead of executable code'; not 4 because the body itself contains no copy-paste-ready code.

3 / 5

Workflow Clarity

The Progressive Complexity table gives a clear sequenced escalation (Basic → Planning → Subagents → Skills) with explicit 'When to add it' decision checkpoints, fitting 'clear sequence with most checkpoints present'; not 5 because there are no validation/feedback loops, and not 3 because the checkpoints are explicit rather than implicit.

4 / 5

Progressive Disclosure

The body is an overview with a categorized '## Resources' section that clearly signals one-level-deep references (agent-philosophy.md, minimal-agent.py, tool-templates.py, subagent-pattern.py, scripts/init_agent.py), all verified to exist, matching the 'clear overview with well-signaled one-level-deep references' anchor.

5 / 5

Total

15

/

20

Passed

Description

78%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.

The description is well-structured with an explicit 'Use when' clause and five concrete trigger scenarios plus a keyword list, giving it strong completeness and trigger coverage. It is slightly broad on capability specificity and has minor overlap risk via the Claude Code/Cursor trigger.

DimensionReasoningScore

Specificity

Names the domain ('AI agents') and two concrete actions ('Design and build') but offers no granular capabilities, matching the 'names domain and 1-2 concrete actions, not comprehensive' anchor; below 4 because coverage is thin and above 2 because actions are concrete rather than generic.

3 / 5

Completeness

Explicitly answers 'what' ('Design and build AI agents for any domain') and 'when' with five numbered concrete trigger phrases under 'Use when users:', exactly matching the 'clearly and explicitly answers both what AND when with concrete trigger phrases' anchor.

5 / 5

Trigger Term Quality

Strong natural keyword coverage ('create an agent', 'build an assistant', 'agent architecture', 'subagents', 'Claude Code', 'Cursor') plus a keyword list with synonyms, fitting 'good keyword coverage; a few natural terms missing'; not 5 because common phrasings like 'chatbot'/'AI bot' and tool-specific extensions are absent.

4 / 5

Distinctiveness Conflict Risk

Clear niche (agent design/building) with distinct triggers and minimal conflict risk, fitting 'mostly distinct; minor overlap risk'; not 5 because the 'ask about Claude Code, Cursor, or similar agent internals' trigger creates minor overlap with general coding skills.

4 / 5

Total

16

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
shareAI-lab/learn-claude-code
Reviewed

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