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 IAPro-Community/Orquestrador-Maestro --skill ralplangit clone --depth 1 https://github.com/IAPro-Community/Orquestrador-MaestroWrote 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/iapro-community/orquestrador-maestro/ralplan)<a href="https://agentmods.dev/skills/iapro-community/orquestrador-maestro/ralplan"><img src="https://agentmods.dev/badge/skills/iapro-community/orquestrador-maestro/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/iapro-community/orquestrador-maestro/ralplan"><img src="https://agentmods.dev/badge/skills/iapro-community/orquestrador-maestro/ralplan.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 Excessive Agency · line 18 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00010 | $0.02344 |
| Opus 5 | $0.00005 | $0.01172 |
| Sonnet 5 | $0.00002 | $0.00469 |
| Haiku 4.5 | $0.00001 | $0.00234 |
Grade A, and why
ralplan 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ralplan (Consensus Planning Alias)
Ralplan is a shorthand alias for $plan --consensus. It triggers iterative planning with Planner, Architect, and Critic agents until consensus is reached, with RALPLAN-DR structured deliberation (short mode by default, deliberate mode for high-risk work).
Usage
$ralplan "task description"
Flags
--interactive: Enables user prompts at key decision points (draft review in step 2 and final approval in step 6). Without this flag the workflow runs fully automated — Planner → Architect → Critic loop — and outputs the final plan without asking for confirmation.--deliberate: Forces deliberate mode for high-risk work. Adds pre-mortem (3 scenarios) and expanded test planning (unit/integration/e2e/observability). Without this flag, deliberate mode can still auto-enable when the request explicitly signals high risk (auth/security, migrations, destructive changes, production incidents, compliance/PII, public API breakage).
Usage with interactive mode
$ralplan --interactive "task description"
Behavior
GPT-5.4 Guidance Alignment
- Default to concise, evidence-dense progress and completion reporting unless the user or risk level requires more detail.
- Treat newer user task updates as local overrides for the active workflow branch while preserving earlier non-conflicting constraints.
- If correctness depends on additional inspection, retrieval, execution, or verification, keep using the relevant tools until the consensus-planning flow is grounded.
- Right-size implementation steps and PRD story counts to the actual scope; do not default to exactly five steps when the task is clearly smaller or larger.
- Continue through clear, low-risk, reversible next steps automatically; ask only when the next step is materially branching, destructive, or preference-dependent.
This skill invokes the Plan skill in consensus mode:
$plan --consensus <arguments>
$plan --consensus --interactive <arguments>
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 · 166 lines · 10 tokens per session scan A 0a77135b5104
ralplan is a skill published in the GitHub repository IAPro-Community/Orquestrador-Maestro (42 stars, last pushed today), licensed Apache-2.0. It adds 10 tokens to every session and 2,344 once invoked, about $0.0001 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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