Agentic Coding

Ship production code with AI agents through acceptance contracts, micro diffs, red green loops, and deterministic handoff checkpoints.

安裝
$clawhub install agentic-coding

Setup

If ~/agentic-coding/ does not exist or is empty, read setup.md, ask a concise kickoff question, and keep any persistence explicitly opt-in.

Positioning

This skill is intentionally different from agentic-engineering and vibe-coding:

  • agentic-engineering focuses on multi-agent operating patterns and team throughput.

  • vibe-coding focuses on prompt-led exploration and fast idea shipping.

  • agentic-coding focuses on contract-first implementation, proof of fix, and reviewer-ready handoff.

When to Use

User needs merge-ready code from an AI agent with explicit quality gates. Use for production features, risky refactors, bug fixes with reproducible failures, and Xcode-centered work such as Swift feature delivery, iOS/macOS regressions, and release-branch hotfixes.

Architecture

Memory lives in ~/agentic-coding/. See memory-template.md for setup.

~/agentic-coding/
|- memory.md       # Persistent preferences and operating mode
|- contracts.md    # Accepted task contracts and non-goals
|- evidence.md     # Test evidence and verification snapshots
`- handoffs.md     # Delivery notes and rollback hints

Quick Reference

Load these files on demand to keep context focused and execution fast.

Topic File
Setup process setup.md
Memory template memory-template.md
PACT loop protocol.md
Contract prompts prompt-contracts.md
Merge handoff checklist handoff.md

Core Rules

1. Lock a Contract Before Writing Code

Start every task with a compact contract:

  • Objective: exact outcome in one sentence

  • Acceptance: checks that prove success

  • Non-goals: what must stay untouched

  • Constraints: stack, style, limits, deadlines

No contract, no code.

2. Run the PACT Loop

Use the same execution loop every time:

  1. Problem framing: restate objective and assumptions

  2. Acceptance design: define checks before edits

  3. Change set: produce the smallest useful diff

  4. Trace and test: show evidence and residual risk

This skill is execution discipline, not brainstorming. For Xcode workflows, tie acceptance to a concrete target, simulator/device, and test command before editing.

3. Keep Diffs Surgical

One user objective maps to one focused change set:

  • Prefer file-local edits over broad rewrites

  • Separate behavior change from style cleanup

  • Avoid hidden side effects outside declared scope

If scope grows, split into a second contract.

4. Prove Failure Then Prove Fix

For bugs and regressions:

  • Capture the failing condition first (test, log, or reproduction)

  • Apply minimal fix

  • Re-run the same check to prove resolution

Never claim fixed without before and after evidence.

5. Deliver Handoff-Grade Output

End each cycle with a delivery packet:

  • What changed and why

  • Files touched and blast radius

  • Validation run and results

  • Known risks and rollback path

If handoff is unclear, the task is not finished.

6. Escalate With a Structured Fallback

When blocked after two failed attempts:

  • Stop editing

  • State what was tried

  • Propose two grounded alternatives

  • Request a decision with tradeoffs

Do not keep guessing in loops.

Common Traps

  • Starting implementation without acceptance checks -> endless iteration and unclear done state.

  • Asking the agent for full rewrites -> noisy diffs and avoidable regressions.

  • Mixing feature work with architecture overhaul -> weak reviewability and hard rollback.

  • Reporting success without reproducible evidence -> false confidence in production.

  • Treating AI output as final draft -> quality debt moved to code review.

Security & Privacy

Data that leaves your machine:

  • None from this skill itself

Data that stays local:

  • Contracts, evidence notes, and handoff summaries in ~/agentic-coding/

This skill does NOT:

  • Trigger undeclared network requests

  • Access files outside its own memory path

  • Write to global or platform memory stores

  • Auto-approve risky code without explicit evidence

Scope

This skill ONLY:

  • Improves execution quality of AI-assisted coding

  • Enforces contract driven implementation and verification

  • Produces clear handoff packets for reviewers

This skill NEVER:

  • Replaces security review for high risk domains

  • Encourages blind trust in generated code

  • Overrides project specific contribution rules

Install with clawhub install <slug> if user confirms:

  • agentic-engineering - Multi-agent collaboration and operating patterns.

  • coding - General coding support across stacks and tasks.

  • code - Broad code authoring and editing assistance.

  • copilot - Companion style IDE assistance patterns.

  • delegate - Structured task delegation to autonomous agents.

Feedback

  • If useful: clawhub star agentic-coding

  • Stay updated: clawhub sync