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 skills add ArisGuimera/MobiAI-Core --skill mobiai-mobile-executing-plans-with-subagentsgit clone --depth 1 https://github.com/ArisGuimera/MobiAI-CoreWrote 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.
[](https://agentmods.dev/skills/arisguimera/mobiai-core/mobiai-mobile-executing-plans-with-subagents)<a href="https://agentmods.dev/skills/arisguimera/mobiai-core/mobiai-mobile-executing-plans-with-subagents"><img src="https://agentmods.dev/badge/skills/arisguimera/mobiai-core/mobiai-mobile-executing-plans-with-subagents/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.
<a href="https://agentmods.dev/skills/arisguimera/mobiai-core/mobiai-mobile-executing-plans-with-subagents"><img src="https://agentmods.dev/badge/skills/arisguimera/mobiai-core/mobiai-mobile-executing-plans-with-subagents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00059 | $0.01035 |
| Opus 5 | $0.00030 | $0.00517 |
| Sonnet 5 | $0.00012 | $0.00207 |
| Haiku 4.5 | $0.00006 | $0.00103 |
Grade A, and why
mobiai-mobile-executing-plans-with-subagents 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mobile Subagent-Driven Development
Execute plan by dispatching fresh subagent per task, with two-stage review after each: spec compliance review first, then code quality review.
Why subagents: Fresh context per task prevents pollution. Precise instructions ensure focus. This preserves your own context for coordination.
Core principle: Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration
When to Use
- Have implementation plan from
mobiai-mobile-planning - Tasks mostly independent
- Want to stay in this session
vs. mobiai-mobile-executing-plans: Same session, fresh subagent per task, two-stage review, faster iteration.
The Process
[Read plan, extract all tasks with full text, create TodoWrite]
For each task:
→ Dispatch implementer subagent
→ Answer questions if any
→ Implementer implements, tests, commits, self-reviews
→ Dispatch spec reviewer subagent
→ If gaps: implementer fixes, spec reviewer re-reviews
→ Dispatch code quality reviewer subagent
→ If issues: implementer fixes, quality reviewer re-reviews
→ Mark task complete in TodoWrite
After all tasks:
→ Dispatch final code reviewer for entire implementation
→ Use mobiai-mobile-finishing-branch
Model Selection
Mechanical tasks (isolated functions, clear specs, 1-2 files): fast, cheap model.
Integration tasks (multi-file coordination, debugging): standard model.
Architecture and review tasks: most capable model.
Handling Implementer Status
DONE: Proceed to spec compliance review.
DONE_WITH_CONCERNS: Read concerns. If about correctness, address before review. If observations, note and proceed.
NEEDS_CONTEXT: Provide missing context and re-dispatch.
BLOCKED: Assess: context problem → provide more. Task too large → break into pieces. Plan wrong → escalate to human.
Never ignore an escalation or force retry without changes.
Prompt Templates
Implementer prompt:
Your task: [exact task text from plan]
Context:
- Platform: [Android/iOS/Flutter/etc.]
- Architecture: [patterns used in project]
- Relevant files: [list]
Instructions:
1. Implement exactly what the task describes
2. Write tests first (TDD: test → fail → implement → pass)
3. Run tests and verify they pass
4. Commit your changes
5. Self-review: completeness, quality, testing
6. Report: Status | What implemented | Test results | Files changed | Issues
Build command: [platform-specific]
Test command: [platform-specific]
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.
- 12d ago First seen · 145 lines · 59 tokens per session scan A 4cb57664cf2d
mobiai-mobile-executing-plans-with-subagents is a skill published in the GitHub repository ArisGuimera/MobiAI-Core (453 stars, last pushed 4d ago), licensed MIT. It adds 59 tokens to every session and 1,035 once invoked, about $0.0003 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 2026-08-30.
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