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 ralphgit 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/ralph)<a href="https://agentmods.dev/skills/iapro-community/orquestrador-maestro/ralph"><img src="https://agentmods.dev/badge/skills/iapro-community/orquestrador-maestro/ralph/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/ralph"><img src="https://agentmods.dev/badge/skills/iapro-community/orquestrador-maestro/ralph.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 151 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 | $0.00014 | $0.03287 |
| Opus 5 | $0.00007 | $0.01643 |
| Sonnet 5 | $0.00003 | $0.00657 |
| Haiku 4.5 | $0.00001 | $0.00329 |
Grade A, and why
ralph 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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- ralph — 88% identical, 17 lines differ
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[RALPH + ULTRAWORK - ITERATION {{ITERATION}}/{{MAX}}]
Your previous attempt did not output the completion promise. Continue working on the task.
<Use_When>
- Task requires guaranteed completion with verification (not just "do your best")
- User says "ralph", "don't stop", "must complete", "finish this", or "keep going until done"
- Work may span multiple iterations and needs persistence across retries
- Task benefits from parallel execution with architect sign-off at the end </Use_When>
<Do_Not_Use_When>
- User wants a full autonomous pipeline from idea to code -- use
autopilotinstead - User wants to explore or plan before committing -- use
planskill instead - User wants a quick one-shot fix -- delegate directly to an executor agent
- User wants manual control over completion -- use
ultraworkdirectly </Do_Not_Use_When>
<Why_This_Exists> Complex tasks often fail silently: partial implementations get declared "done", tests get skipped, edge cases get forgotten. Ralph prevents this by looping until work is genuinely complete, requiring fresh verification evidence before allowing completion, and using tiered architect review to confirm quality. </Why_This_Exists>
<Execution_Policy>
- Fire independent agent calls simultaneously -- never wait sequentially for independent work
- Use
run_in_background: truefor long operations (installs, builds, test suites) - Always pass the
modelparameter explicitly when delegating to agents - Read
docs/shared/agent-tiers.mdbefore first delegation to select correct agent tiers - Deliver the full implementation: no scope reduction, no partial completion, no deleting tests to make them pass
- 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 execution loop is grounded
- Continue through clear, low-risk, reversible next steps automatically; ask only when the next step is materially branching, destructive, or preference-dependent </Execution_Policy>
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.
- 11d ago First seen · 265 lines · 14 tokens per session scan A 470124f3e284
ralph is a skill published in the GitHub repository IAPro-Community/Orquestrador-Maestro (41 stars, last pushed yesterday), licensed Apache-2.0. It adds 14 tokens to every session and 3,287 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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