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/miaodx/intuitive-flow/agent-planning-loopnpx skills add MiaoDX/intuitive-flow --skill agent-planning-loopgit clone --depth 1 https://github.com/MiaoDX/intuitive-flowWrote 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/miaodx/intuitive-flow/agent-planning-loop)<a href="https://agentmods.dev/skills/miaodx/intuitive-flow/agent-planning-loop"><img src="https://agentmods.dev/badge/skills/miaodx/intuitive-flow/agent-planning-loop.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 | $0.00136 | $0.01661 |
| Opus 5 | $0.00068 | $0.00830 |
| Sonnet 5 | $0.00027 | $0.00332 |
| Haiku 4.5 | $0.00014 | $0.00166 |
Grade A, and why
agent-planning-loop 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Planning Loop
Use this skill when the user wants the agent system to do the planning debate before asking for a human decision. It is a bounded orchestration workflow, not an implementation workflow.
The point is to capture the useful 80% of agent suggestions while preventing the remaining 20% from drifting into the wrong product direction. Scout workers generate and challenge options; the main session owns judgment, scope control, and the final recommendation.
Boundary
This skill owns:
- deciding whether a planning loop is worth running;
- dispatching bounded scouts for entropy discovery and document-grounded grill;
- filtering candidates for materiality, product fit, and execution risk;
- iterating once or twice when the first pass exposes a better question;
- returning a compact recommendation set for one user review.
It does not own:
- implementation;
- approving its own plan;
- changing public contracts without user review;
- letting workers ask the user directly;
- running paid, slow, hardware, or credentialed probes unless the user already authorized that cost class.
After approval, route execution back through $intuitive-flow,
$intuitive-refactor, or a concrete worker prompt.
When To Use
Use this loop for fuzzy or contested work where a normal one-shot answer would likely miss important scope:
- a promising idea needs a clearer plan;
- previous conclusions may be overbroad or stale;
- multiple good suggestions need triage;
- docs, tests, metrics, or agent behavior may disagree;
- the user wants workers to run reduce-entropy and grill-batch before bringing them a synthesis.
Do not use it for one-file fixes, simple status checks, obvious bug fixes, or a plan that already has accepted scope and verification.
When the loop is run against an existing plan artifact, assume the plan is the intended execution unit unless the user asks for slice selection or the plan is plainly too broad for their goal. Scouts may recommend phase order, stop gates, or risk isolation, but the main-session recommendation should not quietly shrink the final action to "only implement slice 1." If only a subset is safe, say why full-plan execution is blocked and ask for that decision instead of presenting the subset as the normal next action.
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 · 191 lines · 136 tokens per session scan A 495b664811d0
agent-planning-loop is a skill published in the GitHub repository MiaoDX/intuitive-flow (48 stars, last pushed 8d ago), licensed MIT. It adds 136 tokens to every session and 1,661 once invoked, about $0.0007 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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