A workflow for turning an approved specification into code through planning, implementation, and review. It uses the specification, related wireframes, existing project patterns, and shared utilities as context.

Use it to implement documented screens or components, inspect similar existing code, follow project styling, and review the completed implementation.

It provides a structured path from an agreed design to working code and encourages checking the result against the specification and the rest of the codebase.

ml-impl — Command for Claude Code by jpavley/meta-loop-ios

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo

git clone --depth 1 https://github.com/jpavley/meta-loop-ios

Made for: Claude Code.

Or install meta-loop-ios, the plugin that ships this one along with the rest of its 4 skills, 5 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/commands/jpavley/meta-loop-ios/ml-impl/github.svg)](https://agentmods.dev/commands/jpavley/meta-loop-ios/ml-impl)

Your own site

<a href="https://agentmods.dev/commands/jpavley/meta-loop-ios/ml-impl"><img src="https://agentmods.dev/badge/commands/jpavley/meta-loop-ios/ml-impl/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/commands/jpavley/meta-loop-ios/ml-impl"><img src="https://agentmods.dev/badge/commands/jpavley/meta-loop-ios/ml-impl.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 25 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 2,057 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00025	$0.02057
Opus 5.5	$0.00010	$0.00823
Sonnet 5.5	$0.00005	$0.00411
Haiku 4.5	$0.00003	$0.00206

Measured 1mo ago against content hash d349707e283b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ml-impl scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

commands/ml-impl.md · 344 lines

How it starts

The opening of the file, as written. The whole thing — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Meta-Loop: Implementation Loop

Complete the implementation loop: plan the implementation, write code, and review for correctness.

Modes: Plan Mode → Agent Mode → Ask Mode

Arguments

$ARGUMENTS: Path to the specification to implement
- Examples: specs/views/my-feature/spec.md

Prerequisites

This skill implements Steps 3.1-3.4 of the Meta-Loop process defined in skills/meta-loop-methodology/SKILL.md.

The specification should have already passed /ml-spec review before invoking this skill.

Phase 1: Plan (Plan Mode)

Enter plan mode and create a plan for implementing the specification.

1.1 Load Context

Load the specification from $ARGUMENTS
Load associated wireframes from the same directory
Load notes.md from the same directory (if it exists)
- This file contains decisions from wireframe and spec phases
- Clarifying questions and their answers
- Key decisions and technical notes
Read CLAUDE.md for codebase patterns and conventions
Load referenced view specs (follow links in the spec)
Explore relevant existing code:
- Similar views for patterns
- Shared utilities and helpers
- Theme and styling configuration

1.2 Create the Plan

The plan should outline:

Files to Create:

Full paths for new files
Purpose of each file

Files to Modify:

Full paths for existing files
Summary of changes to each

Implementation Order:

[First step - usually models/types]
[Second step - usually core logic]
[Third step - usually UI components]
[Fourth step - usually integration]
[Fifth step - usually tests]

Testing Strategy:

Unit tests for logic
Preview support for UI components
Integration points to verify

Build Verification:

How to verify the build succeeds
What to test manually

1.3 Present Plan to Developer

Present the plan clearly and wait for developer feedback.

## Implementation Plan

### Specification
`$ARGUMENTS`

### Files to Create
| Path | Purpose |
|------|---------|
| `path/to/NewFile.swift` | [Purpose] |
| ... | ... |

### Files to Modify
| Path | Changes |
|------|---------|
| `path/to/ExistingFile.swift` | [Brief summary] |
| ... | ... |

### Implementation Order
1. **[Step]:** [Details]
2. **[Step]:** [Details]
...

### Testing Strategy
- [ ] [Test approach 1]
- [ ] [Test approach 2]

### Questions for Developer
- [Any clarifications needed before implementing]

Read the full file on GitHub · 344 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 344 lines · 25 tokens per session scan A d349707e283b

Subscribe to this mod's changes

ml-impl is a command published in the GitHub repository jpavley/meta-loop-ios (3 stars, last pushed 7mo ago), licensed MIT. It adds 25 tokens to every session and 2,057 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Claude Code Planning ai-assisted-development claude-code-plugin ios meta-loop swiftui

ml-impl

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

Meta-Loop: Implementation Loop

Arguments

Prerequisites

Phase 1: Plan (Plan Mode)

1.1 Load Context

1.2 Create the Plan

1.3 Present Plan to Developer

What this file has done since we first saw it

Other commands, from other repositories

run-tests

audit

optimize-build

profile

test-simulator

fix-build