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 skills/mtnyilmaz/agents/workflow-executing-plansnpx skills add mtnyilmaz/agents --skill workflow-executing-plansgit clone --depth 1 https://github.com/mtnyilmaz/agentsWrote 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/mtnyilmaz/agents/workflow-executing-plans)<a href="https://agentmods.dev/skills/mtnyilmaz/agents/workflow-executing-plans"><img src="https://agentmods.dev/badge/skills/mtnyilmaz/agents/workflow-executing-plans.svg" alt="Measured on agentmods" 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 | $0.00056 | $0.01588 |
| Opus 5 | $0.00028 | $0.00794 |
| Sonnet 5 | $0.00011 | $0.00318 |
| Haiku 4.5 | $0.00006 | $0.00159 |
Grade A, and why
executing-plans 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 4d 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Executing Plans
Overview
Load the plan, review it critically, execute tasks in order, verify each step, and hand off to the finishing skill. The plan is the source of truth — if you find yourself improvising, stop.
This skill is the inline executor. If your environment supports subagents, prefer workflow-subagent-driven instead — it produces higher-quality output for loosely-coupled tasks.
When to Use
- Plan exists at
.agents/plans/YYYY-MM-DD-<name>.md - Subagents unavailable, or tasks are tightly coupled (each task depends on in-memory context from the previous)
- You want human checkpoints between batches rather than between every task
When NOT to use:
- No plan exists → use
workflow-writing-plansfirst - Tasks are independent and subagents are available → use
workflow-subagent-driven - Single-file trivial change → just do it, no plan needed
The Workflow
Load plan ─→ Critical review ─→ Create TodoWrite ─→ Execute task loop ─→ Finishing skill
│ │
▼ ▼
Raise concerns Per task: follow steps
before starting exactly, run verifications,
mark complete
Step 1 — Load and Review the Plan
- Read the plan file end to end.
- Review critically. Before executing anything, ask yourself:
- Does every task have the code, verification command, and commit written out?
- Are type/name usages consistent across tasks?
- Any placeholders (
TBD,TODO,similar to,appropriate)? - Does the plan violate universal rules (soft delete, i18n,
@latest, Route→Service→DB)?
- If you find problems → stop and raise them with the human before starting. Don't patch a broken plan silently.
- If the plan is clean → create a TodoWrite with one entry per task, mark the first as
in_progress, continue.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 150 lines · 56 tokens per session scan A 8de9766c3517
executing-plans is a skill published in the GitHub repository mtnyilmaz/agents (6 stars, last pushed 3mo ago), licensed MIT. It adds 56 tokens to every session and 1,588 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 2026-08-31.
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