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 ApexIQ/skillsmith --skill atomic_executiongit clone --depth 1 https://github.com/ApexIQ/skillsmithWrote 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/apexiq/skillsmith/atomic_execution)<a href="https://agentmods.dev/skills/apexiq/skillsmith/atomic_execution"><img src="https://agentmods.dev/badge/skills/apexiq/skillsmith/atomic_execution/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/apexiq/skillsmith/atomic_execution"><img src="https://agentmods.dev/badge/skills/apexiq/skillsmith/atomic_execution.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00018 | $0.00455 |
| Opus 5 | $0.00009 | $0.00228 |
| Sonnet 5 | $0.00004 | $0.00091 |
| Haiku 4.5 | $0.00002 | $0.00046 |
Grade A, and why
atomic_execution 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 7d 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.
What it actually says
Atomic Execution Workflow
Use this workflow for every coding task to ensure quality and prevent "Agent Hallucinations".
The Loop
- Discuss (Review)
- Plan
- Execute
- Verify
1. Discuss (Review)
Before writing code, understand the context.
- Read
.agent/STATE.md. - Read relevant source files.
- Ask clarifying questions if requirements are vague.
2. Plan (The Blueprints)
Create a specific plan for this specific task. Do not generic plan.
- For complex tasks: Create/Update
.agent/plans/current_task.md. - For simple tasks: Output a markdown checklist in the chat.
Checklist Format:
- [ ] Create `file_a.py` with function `x`.
- [ ] Update `file_b.py` to import `x`.
- [ ] Run test `test_x.py` to verify.
3. Execute (Atomic Steps)
Write code in small, verifiable chunks.
- Do not write 5 files at once.
- Do write one module, then the next.
- Do use
edit_fileorwrite_filetools precisely. - Rule: If you edit a file, you must know its current content (read it first).
4. Verify (Trust, but Verify)
Never claim a task is done without proof.
- Compile/Lint: Run the build command.
- Test: Run specific unit tests (
pytest tests/test_feature.py). - Manual Check: If UI, verify the component renders (conceptually or via screenshots if available).
Completion
Once verified:
- Update
.agent/STATE.md. - Mark the item as done in
.agent/ROADMAP.md(if applicable). - Notify the user.
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.
- 7d ago First seen · 66 lines · 18 tokens per session scan A 2a66d8785342
atomic_execution is a skill published in the GitHub repository ApexIQ/skillsmith (5 stars, last pushed 5mo ago), licensed MIT. It adds 18 tokens to every session and 455 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 2026-09-03.
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