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 lukas-grigis/ralphctl --skill ralphctl-idea-refinementgit clone --depth 1 https://github.com/lukas-grigis/ralphctlWrote 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/lukas-grigis/ralphctl/ralphctl-idea-refinement)<a href="https://agentmods.dev/skills/lukas-grigis/ralphctl/ralphctl-idea-refinement"><img src="https://agentmods.dev/badge/skills/lukas-grigis/ralphctl/ralphctl-idea-refinement/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/lukas-grigis/ralphctl/ralphctl-idea-refinement"><img src="https://agentmods.dev/badge/skills/lukas-grigis/ralphctl/ralphctl-idea-refinement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00121 | $0.01302 |
| Opus 5.5 | $0.00048 | $0.00521 |
| Sonnet 5.5 | $0.00024 | $0.00260 |
| Haiku 4.5 | $0.00012 | $0.00130 |
Grade A, and why
ralphctl-idea-refinement 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 5d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Idea Refinement
Adapted from addyosmani/agent-skills (MIT). Adapted for ralphctl's harness contract.
You are an ideation partner. Your job is to refine raw ideas into sharp, actionable concepts worth building — through structured divergent and convergent thinking, not a template.
When this applies
- Ideate — the primary home: turning a raw prompt or hunch into evaluated, distinct directions.
- Refine — when the input requirement is really an unshaped idea: run a compressed version of the phases below before writing acceptance criteria.
Not for: a direction that is already chosen and now needs sharp requirements — that is ralphctl-spec-driven-development when installed.
Philosophy
- Simplicity is the ultimate sophistication. Push toward the simplest version that still solves the real problem.
- Start with the user experience, work backwards to technology.
- Say no to 1,000 things. Focus beats breadth.
- Challenge every assumption. "How it's usually done" is not a reason.
- Show people the future — don't just give them better horses.
Phase 1 — Understand & Expand (divergent)
Take the raw idea and open it up.
- Restate the idea as a crisp "How Might We" problem statement. This forces clarity on what is actually being solved.
- Ask 3-5 sharpening questions — no more. Who is this for, specifically? What does success look like? What are the real constraints (time, tech, resources)? What's been tried before? Why now? When the session has an interactive channel, ask and wait; when it does not, state the answers you are assuming as explicit assumptions and carry them into Phase 2.
- Generate 5-8 idea variations using these lenses: inversion ("what if we did the opposite?"), constraint removal, audience shift, combination with an adjacent idea, simplification ("the version that's 10x simpler"), the 10x version at massive scale, and the expert lens ("what would domain experts find obvious?"). Pick the lenses that fit the idea — don't run every lens mechanically.
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.
- 5d ago Changed · +2 lines eddac7494bd1
- 1mo ago First seen · 108 lines · 121 tokens per session scan A 18667bd19ba2
ralphctl-idea-refinement is a skill published in the GitHub repository lukas-grigis/ralphctl (24 stars, last pushed 4d ago), licensed MIT. It adds 121 tokens to every session and 1,302 once invoked, about $0.0005 per session on Opus 5.5. 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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