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SKILL unreviewed Apache-2.0 Self-run

Running Skills Edd Cycle

skill-taisukeoe-agentic-ai-skills-creator-running-skills-edd-cycle · by taisukeoe

Guides evaluation-driven development (EDD) process for agent skills. Use when setting up skill testing workflows, creating skill evaluation scenarios, or establishing Claude A/B feedback loops for skill validation. Provides development methodology, not content guidance.

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Install

$ agentstack add skill-taisukeoe-agentic-ai-skills-creator-running-skills-edd-cycle

Open-source listing, not yet scanned by AgentStack. Follow the source repository for install instructions.

Security review

⚠ Flagged

1 finding(s); flagged for manual review. · v0.1.0 How review works →

  • • Prompt-injection patterns
  • • Secret / credential exfiltration
  • • Dangerous shell & filesystem operations
  • • Untrusted network calls
  • • Known-malicious package signatures
  • high Dangerous shell/eval execution.

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ● Dynamic code execution Used

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Reliability & compatibility

— Not yet reviewed
0 installs to date
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○ 8mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

Running Skills EDD Cycle

Run evaluation-driven development cycle for agent skills.

Workflow

Step 1: Build Evaluations First

Create evaluations BEFORE writing documentation. This ensures skills solve real problems.

  1. Run Claude on representative tasks WITHOUT the skill
  2. Document specific failures or missing context
  3. Create 3+ evaluation scenarios that test these gaps

Evaluation scenarios are saved to tests/scenarios.md as the final step of /creating-effective-skills workflow.

Step 2: Establish Baseline

Measure Claude's performance WITHOUT the skill:

  1. Run each evaluation scenario
  2. Record: success/failure, missing context, wrong approaches
  3. This becomes comparison baseline

Step 3: Write Minimal Instructions

Create just enough content to address the gaps:

  • Start with core workflow only
  • Add detail only when tests fail
  • Avoid over-explaining

REQUIRED: Use the Skill tool to invoke creating-effective-skills before writing any skill content. This ensures proper naming, description format, and structure from the start.

Step 4: Evaluate with Multiple Models

> Note: This step requires Claude Code CLI. Skip if using Claude.ai.

REQUIRED: Use the Skill tool to invoke evaluating-skills-with-models with the skill path.

This will:

  1. Auto-load scenarios from tests/scenarios.md
  2. Execute with sub-agents across models (sonnet, opus, haiku)
  3. Evaluate against expected behaviors
  4. Determine recommended model (least capable with full compatibility)

After evaluation: Document recommended model in skill's metadata.

REQUIRED: Use the Skill tool to invoke improving-skills when observations reveal issues.

Step 5: Final Review

Before considering the skill complete:

REQUIRED: Use the Skill tool to invoke reviewing-skills to verify compliance with best practices.

  1. Address all compliance issues identified
  2. Re-run evaluations after fixes
  3. Repeat until skill passes review

Step 6: User Validation Guide

After all reviews pass, output instructions for user to validate in a fresh session:

## Test Your Skill

Run this command in a new terminal to test with a fresh Claude session:

claude --model {recommended_model} "{evaluation_query}"

After testing, paste the output file or result back to this session for final confirmation.

Replace:

  • {recommended_model}: Model determined in Step 4 (e.g., sonnet)
  • {evaluation_query}: A representative query from your evaluations

Quick Reference

Cycle

Identify gaps -> Create evaluations -> Baseline -> Write minimal -> Model eval (sub-agents) -> Review -> User validation

What Observations Indicate

| Observation | Indicates | |-------------|-----------| | Unexpected file reading order | Structure not intuitive | | Missed references | Links need to be explicit | | Repeated reads of same file | Move content to SKILL.md | | Never accessed file | Unnecessary or poorly signaled |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.