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 tobihagemann/turbo --skill refine-plangit clone --depth 1 https://github.com/tobihagemann/turboWrote 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/tobihagemann/turbo/refine-plan)<a href="https://agentmods.dev/skills/tobihagemann/turbo/refine-plan"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/refine-plan/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/tobihagemann/turbo/refine-plan"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/refine-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 12 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00049 | $0.01902 |
| Opus 5 | $0.00024 | $0.00951 |
| Sonnet 5 | $0.00010 | $0.00380 |
| Haiku 4.5 | $0.00005 | $0.00190 |
Grade A, and why
refine-plan 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Refine Plan
Loop the review pipeline over a plan until no new findings are accepted. Writes back to the plan file in place.
Task Tracking
At the start of every invocation (including re-runs from Step 5), use TaskCreate to create a task for each step:
- Resolve the plan
- Run
/review-planskill - Run
/evaluate-findingsskill - Run
/apply-findingsskill - Re-run
/refine-planskill if changed
Step 1: Resolve the Plan
- Explicit path — use it
- Explicit slug — resolve to
.turbo/plans/<slug>.md - Single file — Glob
.turbo/plans/*.md. If exactly one file exists, use it - Most recent — most recently modified file
- Legacy fallback —
.turbo/plan.mdif.turbo/plans/does not exist - Nothing found — tell the user to run
/turboplanand stop
If multiple candidates exist and the choice is non-obvious, use AskUserQuestion.
State the resolved path before continuing.
Unless an explicit path or slug was passed, confirm the resolved plan still describes work that remains to be done. The signal is a frontmatter status: of done.
When the signal fires, output it as text. Then use AskUserQuestion to offer:
- Refine anyway — the marker is stale
- Pick another plan — resolve to a different file under
.turbo/plans/, then confirm that plan against this same signal - Leave the plan alone — skip refining
On Leave the plan alone, mark the remaining refine steps deleted, then use the TaskList tool and proceed to any remaining task.
Step 2: Run /review-plan Skill
Run the /review-plan skill on the resolved plan.
Always run this step even if the plan looks polished.
Step 3: Run /evaluate-findings Skill
Run the /evaluate-findings skill on the review findings from Step 2.
Step 4: Run /apply-findings Skill
Run the /apply-findings skill on the evaluated results.
Step 5: Re-run /refine-plan Skill if Changed
Check whether the plan file was edited during Step 4. Any edit counts.
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 · 97 lines · 49 tokens per session scan A 251dc3c4d37c
refine-plan is a skill published in the GitHub repository tobihagemann/turbo (402 stars, last pushed 3d ago), licensed MIT. It adds 49 tokens to every session and 1,902 once invoked, about $0.0002 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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