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djc00p

Agentic Engineering

by Deonte Cooper · GitHub ↗ · v1.0.0 · MIT-0
linuxdarwinwin32 ✓ Security Clean
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Install in OpenClaw
/install agentic-engineering-ecc
Description
Workflow pattern for AI-assisted engineering using eval-first execution, task decomposition, and cost-aware model routing. Trigger phrases: agentic engineeri...
README (SKILL.md)

Agentic Engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Adapted from everything-claude-code by @affaan-m (MIT).

Quick Start

  1. Define completion criteria — write acceptance criteria and success metrics before execution
  2. Create baseline evals — write capability and regression tests that capture current state
  3. Decompose work — break into 15-minute units, each independently verifiable with a single dominant risk
  4. Route models by complexity — Haiku for narrow tasks, Sonnet for implementation, Opus for architecture
  5. Run post-implementation evals — measure deltas, confirm no regressions

Key Concepts

  • Eval-first execution: Run tests before coding; measure against known baseline; catch regressions early
  • 15-minute unit rule: Each task should have one clear risk, one verifiable outcome, be completable in ~15 minutes
  • Model tier matching: Complexity determines model — don't overpay for simple tasks, don't underpay for hard ones
  • Review focus: Prioritize invariants, error boundaries, security, coupling — not style (automation handles that)
  • Session strategy: Continue for coupled units; reset after major phase transitions; compact at milestones

Common Usage

Setting up eval-first for a feature:

1. Define acceptance criteria (user-facing behavior)
2. Write capability eval (can the system do the required task?)
3. Write regression eval (does existing functionality still work?)
4. Execute feature implementation with model routing
5. Re-run evals, compare deltas
6. Document any new risks discovered during review

Model routing example:

  • Haiku: boilerplate generation, narrow edits, classification
  • Sonnet: feature implementation, small refactors, test writing
  • Opus: multi-file changes, root-cause analysis, architecture decisions

Cost discipline: Track per task: model tier, token estimate, retries, wall-clock time, success/failure. Escalate model tier only when lower tier fails with clear reasoning gap, not on uncertainty.

References

  • references/eval-patterns.md — detailed eval-first loop patterns
  • references/decomposition-rules.md — 15-minute unit principle and task breakdown examples
  • references/review-checklist.md — what to focus on in code review (invariants, boundaries, security, coupling)
Usage Guidance
This skill is a set of best-practice instructions (eval-first, 15-minute units, model-tier routing) and contains no code, installs, or credential requests—so it is internally coherent. Before enabling: confirm you understand the platform's model access and billing (the skill recommends routing to model tiers named Haiku/Sonnet/Opus but does not provision them), avoid feeding sensitive secrets into prompts when testing, and consider whether you want the agent to invoke skills autonomously (the platform default) in your environment. If you need higher assurance, ask the author for provenance or run the guidance in a sandbox before applying it to real projects.
Capability Analysis
Type: OpenClaw Skill Name: agentic-engineering-ecc Version: 1.0.0 The skill bundle provides a structured workflow for AI-assisted engineering, focusing on evaluation-driven development, task decomposition, and cost-aware model routing. The instructions in SKILL.md and the reference files (decomposition-rules.md, eval-patterns.md, review-checklist.md) are purely methodological and do not contain any malicious commands, data exfiltration logic, or prompt injection attacks designed to subvert the agent's behavior.
Capability Assessment
Purpose & Capability
Name/description (agentic engineering, eval-first, decomposition, model routing) matches the content of SKILL.md and reference files; nothing in the package asks for unrelated capabilities (no cloud creds, no unusual binaries).
Instruction Scope
SKILL.md and references limit themselves to process guidance (write evals, decompose tasks, route by model tier, review checklist). They do not instruct the agent to read arbitrary files, export secrets, or call external endpoints.
Install Mechanism
No install spec and no code files—this is instruction-only, so nothing is downloaded or written to disk during installation.
Credentials
The skill declares no environment variables, credentials, or config paths; the guidance about model tiers is conceptual and does not require additional secrets from the user.
Persistence & Privilege
always:false (default) and no install actions that modify agent state are present. The skill is user-invocable and can be invoked autonomously by the agent (platform default), which is expected for skills of this type.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agentic-engineering-ecc
  3. After installation, invoke the skill by name or use /agentic-engineering-ecc
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release. Eval-first agentic execution patterns with 15-min task units and model routing tiers. Adapted from everything-claude-code by @affaan-m (MIT)
Metadata
Slug agentic-engineering-ecc
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Agentic Engineering?

Workflow pattern for AI-assisted engineering using eval-first execution, task decomposition, and cost-aware model routing. Trigger phrases: agentic engineeri... It is an AI Agent Skill for Claude Code / OpenClaw, with 137 downloads so far.

How do I install Agentic Engineering?

Run "/install agentic-engineering-ecc" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agentic Engineering free?

Yes, Agentic Engineering is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Agentic Engineering support?

Agentic Engineering is cross-platform and runs anywhere OpenClaw / Claude Code is available (linux, darwin, win32).

Who created Agentic Engineering?

It is built and maintained by Deonte Cooper (@djc00p); the current version is v1.0.0.

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