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.
npx agentmods add commands/jpavley/meta-loop-ios/ml-implgit clone --depth 1 https://github.com/jpavley/meta-loop-iosWhat 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 | $0.00025 | $0.02057 |
| Opus 5 | $0.00013 | $0.01028 |
| Sonnet 5 | $0.00005 | $0.00411 |
| Haiku 4.5 | $0.00003 | $0.00206 |
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 yesterday.
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.
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
- Examples:
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
$ARGUMENTS - Load associated wireframes from the same directory
- Load
notes.mdfrom the same directory (if it exists)- This file contains decisions from wireframe and spec phases
- Clarifying questions and their answers
- Key decisions and technical notes
- Read CLAUDE.md for codebase patterns and conventions
- Load referenced view specs (follow links in the spec)
- Explore relevant existing code:
- Similar views for patterns
- Shared utilities and helpers
- Theme and styling configuration
1.2 Create the Plan
The plan should outline:
Files to Create:
- Full paths for new files
- Purpose of each file
Files to Modify:
- Full paths for existing files
- Summary of changes to each
Implementation Order:
- [First step - usually models/types]
- [Second step - usually core logic]
- [Third step - usually UI components]
- [Fourth step - usually integration]
- [Fifth step - usually tests]
Testing Strategy:
- Unit tests for logic
- Preview support for UI components
- Integration points to verify
Build Verification:
- How to verify the build succeeds
- What to test manually
1.3 Present Plan to Developer
Present the plan clearly and wait for developer feedback.
## Implementation Plan
### Specification
`$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]
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.
- yesterday First seen · 344 lines · 25 tokens per session scan A d349707e283b
ml-impl is a command published in the GitHub repository jpavley/meta-loop-ios (3 stars, last pushed 6mo ago), licensed MIT. It adds 25 tokens to every session and 2,057 once invoked, about $0.0001 per session on Opus 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.
Other commands, from other repositories
OPSX: Explore
Enter explore mode - think through ideas, investigate problems, clarify requirements.
OPSX: Apply
Implement tasks from an OpenSpec change (Experimental).
OPSX: Archive
Archive a completed change in the experimental workflow.
OPSX: Propose
Propose a new change - create it and generate all artifacts in one step.
OPSX: Sync
Sync delta specs from a change to main specs.
status
Project health dashboard - shows environment status and suggests improvements.