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 hg-pyun/claude-code-marketplace --skill ralplangit clone --depth 1 https://github.com/hg-pyun/claude-code-marketplaceWrote 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/hg-pyun/claude-code-marketplace/ralplan)<a href="https://agentmods.dev/skills/hg-pyun/claude-code-marketplace/ralplan"><img src="https://agentmods.dev/badge/skills/hg-pyun/claude-code-marketplace/ralplan/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/hg-pyun/claude-code-marketplace/ralplan"><img src="https://agentmods.dev/badge/skills/hg-pyun/claude-code-marketplace/ralplan.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00145 | $0.09116 |
| Opus 5 | $0.00072 | $0.04558 |
| Sonnet 5 | $0.00029 | $0.01823 |
| Haiku 4.5 | $0.00015 | $0.00912 |
Grade C, and why
ralplan scanned grade C with 1 finding 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 9d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- destructive (delete, drop, truncate, rm -rf, force) How it starts
The opening of the file, as written. The whole thing — 298 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The non-negotiable invariant is adversarial blind-spot elimination = author ≠ attacker: the agent that authors a candidate is never the agent that attacks it, and the synthesizer is distinct from every attacker. This separation is enforced by dispatch topology (different subagent_type in different Task calls). What that structurally guarantees is narrow but real — no single context ever authors and then approves its own work. Independence beyond that (that the separate attacker/synthesizer does not share the author's systematic blind spots) is strengthened by orthogonal lenses + model diversity, but is a prose-enforced convention, not a harness-level code gate.
<Use_When>
- A spec (
.dt-handoff/<slug>/spec.md, or an ad-hoc description) needs a vetted implementation plan before any code is written. - User invokes
/ralplan, says "ralplan", "plan this with consensus", "합의 계획 잡아줘". - The work involves architectural choices, migrations, or high-risk areas (auth, security, destructive changes) and warrants a wider panel + pre-mortem + expanded test planning (auto-detected → HIGH tier).
autopilotPhase 2 (Planning) calls this skill as a sub-step. </Use_When>
<Do_Not_Use_When>
- The user wants execution, not planning — route to
ralphorautopilot. - The user wants requirements capture (WHAT, not HOW) rather than a plan — clarify the requirements into a spec first, then return to ralplan.
- The user wants a one-shot bug fix or trivial change with no design choice — delegate to
executordirectly (ralplan will still run a minimal N=1 panel if invoked, but it is overkill). - The user wants free-form brainstorming with no committed artifact — answer directly without invoking ralplan.
- The user wants severity-rated review of an existing plan — use
code-revieworcriticdirectly. </Do_Not_Use_When>
<Why_This_Exists> Plans written by one author and approved by the same author share that author's blind spots — they overweight the chosen approach and underweight alternatives. The classic fix (one draft, then a reviewer) only weakens this; the draft still anchors the whole deliberation. A panel of independent candidates, each grown from a different starting framing and each attacked by a separate adversary, eliminates blind spots structurally rather than behaviorally: there is no single draft to anchor on, and no agent ever grades its own work.
Two corrections make the separation real rather than cosmetic. First, candidate authorship belongs to architect, not planner: planner explicitly refuses design judgment and delegates it, while architect is the agent that produces multi-option/trade-off analysis. Second, decorrelation must be real — identical-weight models share systematic blind spots ("capability symmetry ≠ judgment independence"), so the attacker is decorrelated from the author by an orthogonal attack lens and, when the runtime allows per-dispatch model selection, by a different model tier.
Risk-proportional depth replaces the old cost machinery (mode-gate / Critic-input-set / model-routing / Dispatch Ledger), whose savings were never observed in practice. A single dial — risk tier — sets panel width, attack depth, and whether a pre-mortem runs. Cost is controlled by three visible knobs (N, attack-lens count, model tier), not by conditional fast-paths.
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.
- 9d ago First seen · 298 lines · 145 tokens per session scan C 0e2a725f8042
ralplan is a skill published in the GitHub repository hg-pyun/claude-code-marketplace (2 stars, last pushed 2mo ago), licensed MIT. It adds 145 tokens to every session and 9,116 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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