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 agentmods add skills/aigentive/ralphx/ralphx-agent-workflow-orchestratornpx skills add aigentive/RalphX --skill ralphx-agent-workflow-orchestratorgit clone --depth 1 https://github.com/aigentive/RalphXWrote 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/aigentive/ralphx/ralphx-agent-workflow-orchestrator)<a href="https://agentmods.dev/skills/aigentive/ralphx/ralphx-agent-workflow-orchestrator"><img src="https://agentmods.dev/badge/skills/aigentive/ralphx/ralphx-agent-workflow-orchestrator.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.00482 |
| Opus 5 | $0.00015 | $0.00241 |
| Sonnet 5 | $0.00006 | $0.00096 |
| Haiku 4.5 | $0.00003 | $0.00048 |
Grade A, and why
ralphx-agent-workflow-orchestrator 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 6d 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 — 27 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RalphX Agent Workflow Orchestrator
Use this skill only in a conversation whose selected capability is Workflow.
Generate a deterministic JavaScript program for the bundled RalphX workflow runner. The program may use only the provided globals: args, meta, phase, log, agent, parallel, pipeline, and checkpoint helpers. It has no filesystem, shell, network, environment, process, import, or module access.
Authoring contract
- Break the request into named phases and call
phase(name)before each phase. - Give every
agent()call a stablelogicalKey. A key must identify the same prompt and output schema across retries. - Keep prompts self-contained. Do not interpolate untrusted text into executable JavaScript; pass user values through
args. - Use explicit JSON Schemas for machine-consumed results. A schema makes the delegated agent return JSON-only output; RalphX validates it before caching/completing the invocation and exposes the parsed value as
result.content. Missing, null, extra (when disallowed), or type-invalid required results fail the workflow. - Keep fanout within the declared
maxConcurrencyandmaxInvocationsmetadata. Prefer the smallest useful fanout. - Use
parallel([{ prompt, logicalKey, agentName, schema, title }, ...])only for independent agent work; this descriptor form is the backend-enforced concurrent fanout path. Usepipeline()when later work depends on earlier output. - End with a concise structured result that can be reported truthfully to the user.
Call create_agent_workflow_script with the script, metadata, permission summary, and estimated fanout. This stores the script for user review; it never approves or starts it. Do not claim that a workflow is running until start_agent_workflow_run succeeds after the user-approved hash is present.
Use the run inspection and pause/resume/cancel tools for lifecycle management. Never expose or invent runner attempts, leases, transport frames, delegated job IDs, or recovery bookkeeping.
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.
- 6d ago First seen · 27 lines · 30 tokens per session scan A a8d711bb2966
ralphx-agent-workflow-orchestrator is a skill published in the GitHub repository aigentive/RalphX (5 stars, last pushed 6d ago), licensed Apache-2.0. It adds 30 tokens to every session and 482 once invoked, about $0.0002 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 2026-08-31.
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