CtrlK
BlogDocsLog inGet started
Tessl Logo

agent-designer

Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).

72

Quality

88%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is agent-designer in alirezarezvani/claude-skills

SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

Tightly written with excellent workflow sequencing, explicit validation checkpoints, and a recovery feedback loop. The major weakness is bundle integrity: every referenced script, asset, and reference file is missing, which undermines both executability and the progressive-disclosure navigation the body promises.

Suggestions

Ship the referenced bundle so the disclosed navigation resolves: create references/agent_architecture_patterns.md, references/tool_design_best_practices.md, references/evaluation_methodology.md, the three assets/sample_*.json files, expected_outputs/, and the agent_planner.py / tool_schema_generator.py / agent_evaluator.py scripts.

If any referenced artifact is intentionally not bundled, say so inline (e.g. "generate locally" vs "copy assets/...") so Claude does not chase a missing file.

Once the bundle exists, re-verify that the --validate / 0-critical-issues gates in step 4 correspond to real script output so the feedback loop is runnable as written.

DimensionReasoningScore

Conciseness

The body is lean throughout — a compact pattern table, one command plus a one-line output description per step — and assumes Claude's competence without explaining concepts it already knows; every section earns its tokens.

5 / 5

Actionability

Concrete, flag-specific commands (e.g. "python3 agent_planner.py requirements.json --format json -o arch") with named outputs are mostly copy-paste ready, but the referenced scripts and sample assets (agent_planner.py, assets/sample_tool_descriptions.json) are absent from the bundle, leaving a real executability gap that keeps it below 5.

4 / 5

Workflow Clarity

A clearly sequenced four-step workflow culminates in a verification loop with explicit checkpoints and a feedback loop ("If N > 0, apply the top item in eval_recommendations.json, re-run the pilot, and re-evaluate"), matching the clear-sequence-with-validation-and-feedback anchor.

5 / 5

Progressive Disclosure

The writing is well structured as an overview pointing one level deep to references/ and assets/, but scoring against the actual bundle per the rubric guideline reveals that none of the referenced files (references/*.md, assets/*.json, expected_outputs/, and the three .py scripts) exist, so the signaled navigation is effectively broken.

3 / 5

Total

17

/

20

Passed

Description

92%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 strong, specific description with explicit trigger phrases, concrete example utterances, and clear disambiguation against neighboring skills. The only soft spot is trigger-term breadth, which is good but not exhaustively synonym-rich.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks" — each with specific sub-elements, giving comprehensive coverage rather than the minor-gaps level of 4.

5 / 5

Completeness

Explicitly answers both what (design / schema-generate / evaluate multi-agent systems) and when ("Use when the user asks to..." plus three concrete example trigger phrases), matching the both-what-and-when-with-concrete-triggers anchor.

5 / 5

Trigger Term Quality

Natural user phrases are supplied as examples ("design an agent architecture for research automation", "generate Anthropic tool schemas", "analyze these agent run logs for bottlenecks"), giving good keyword coverage, but it stops short of the comprehensive synonym/extension breadth of a 5 and leans on specialized terms.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche and adds explicit boundary guidance — "NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer)" — minimizing conflict with adjacent skills.

5 / 5

Total

19

/

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 6 missing

Warning

Total

15

/

16

Passed

Repository
alirezarezvani/claude-skills
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.