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 juicesharp/rpiv-mono --skill quick-plangit clone --depth 1 https://github.com/juicesharp/rpiv-monoWrote 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/juicesharp/rpiv-mono/quick-plan)<a href="https://agentmods.dev/skills/juicesharp/rpiv-mono/quick-plan"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/quick-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/juicesharp/rpiv-mono/quick-plan"><img src="https://agentmods.dev/badge/skills/juicesharp/rpiv-mono/quick-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 MCP Rug Pull · line 156 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 157 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00120 | $0.02902 |
| Opus 5 | $0.00060 | $0.01451 |
| Sonnet 5 | $0.00024 | $0.00580 |
| Haiku 4.5 | $0.00012 | $0.00290 |
Grade A, and why
quick-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 10d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quick Plan
You produce a single, unsliced, consistently-phased implementation plan for a small, well-understood task and write it directly to .rpiv/artifacts/plans/ with status: ready. One non-interactive pass — no slice decomposition, no skeleton-then-fill, no in-skill review. The workflow's grade and validate stages (or your own review, standalone) are the gates; this skill only emits the artifact those gates parse.
The expected shape is one phase (the small-task default). Add a phase only when the task genuinely splits into independently-verifiable units that share no file. This is the trimmed mimic of blueprint's artifact shape minus every step that exists to produce confidence in the artifact.
Input
$ARGUMENTS — one of four shapes (the skill is sound however the caller wires it):
- Flags (workflow dispatch) —
--research <path> --goal <path> [--acceptance <path>]. Read ALL files FULLY (no limit/offset). The research doc is the grounding; the goal file is the verbatim brief — every ask it names is either implemented by a phase or deferred under## Out of Scope. The acceptance file, when given, is the goal-derived inventory (items:frontmatter, idsa1…): the plan MUST record a per-itemacceptance:disposition —implementednaming the phase, ordeferredwith a reason — every item, no omissions (the completeness gate anchors on the inventory, and validate executes each item's evidence command against the finished tree). - Research artifact path — a
.mdpath under.rpiv/artifacts/research/. Read it FULLY (no limit/offset); it is the grounding for the plan. - Injected research — when dispatched by a workflow
reads: ["research"]stage, the research doc is already in context; treat$ARGUMENTSas the task description / goal. - Free-text (standalone small task) —
$ARGUMENTSis the task description; research is done or the shape is obvious.
If $ARGUMENTS is empty AND no research doc is in context, print an error and stop — there is nothing to plan from.
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.
- 10d ago First seen · 183 lines · 120 tokens per session scan A 5609315cecf1
quick-plan is a skill published in the GitHub repository juicesharp/rpiv-mono (773 stars, last pushed yesterday), licensed MIT. It adds 120 tokens to every session and 2,902 once invoked, about $0.0006 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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