homerail-dag-ops

homerail-dag-ops is a skill for Codex from xiaotianfotos/homerail. It costs 153 tokens per session (4,248 once invoked), scanned A, original, MIT.

A command-line toolkit for running and managing HomeRail DAG workflows. A DAG is a workflow made of connected steps, and it can include several supervised actors working on separate parts of a task.

In plain words
What is it for?
Use it to list workflow templates, start and monitor runs, inspect chats and handoffs, and follow up with individual actors. It also supports live panels for evidence research, skeptical analysis, and publication drafts.
Why use it?
It brings starting, watching, inspecting, debugging, and continuing complex workflows into one interface. This reduces the need to track separate runs and actor conversations manually.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Claude Code.

Good fit Use it to list workflow templates, start and monitor runs, inspect chats and handoffs, and follow up with individual actors. It also supports live panels for evidence research, skeptical analysis, and publication drafts.

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Install with agentmods
npx agentmods add skills/xiaotianfotos/homerail/homerail-dag-ops
Install

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.

Any agent
npx skills add xiaotianfotos/homerail --skill homerail-dag-ops
Clone the repo
git clone --depth 1 https://github.com/xiaotianfotos/homerail

Made for: Codex.

Wrote 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.

agentmods badge for homerail-dag-ops

README.md
[![agentmods](https://agentmods.dev/badge/skills/xiaotianfotos/homerail/homerail-dag-ops/github.svg)](https://agentmods.dev/skills/xiaotianfotos/homerail/homerail-dag-ops)
Your own site
<a href="https://agentmods.dev/skills/xiaotianfotos/homerail/homerail-dag-ops"><img src="https://agentmods.dev/badge/skills/xiaotianfotos/homerail/homerail-dag-ops/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.

agentmods 80×15 button for homerail-dag-ops

Your own site · 80×15
<a href="https://agentmods.dev/skills/xiaotianfotos/homerail/homerail-dag-ops"><img src="https://agentmods.dev/badge/skills/xiaotianfotos/homerail/homerail-dag-ops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 153 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,248 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00153 $0.04248
Opus 5 $0.00077 $0.02124
Sonnet 5 $0.00031 $0.00850
Haiku 4.5 $0.00015 $0.00425

Measured 13d ago against content hash f9ce6c176a34, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

homerail-dag-ops scanned grade A 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 13d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s "$HOMERAIL_MANAGER_URL/api/dag-status/<run_id>/node/<node_id>/result"
skills/homerail-dag-ops/SKILL.md · 441 lines

How it starts

The opening of the file, as written. The whole thing — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.

HomeRail DAG Operations (TypeScript Backend)

Before acting, apply homerail-shared rules. This skill assumes the local runtime is already ready. If not, run hr start or use homerail-install-ops.

When this Skill is loaded inside the HomeRail Manager Agent, use the harness's native shell and the HomeRail CLI whenever they provide the clearest or most complete path. Prefer --json so command results remain structured. Dedicated Manager Tools such as list_orchestrations, create_and_run, invoke_run, and get_run_status are equivalent shorter paths for operations they already cover; they are not the only valid execution route. For abstract pattern selection, load homerail-dag-patterns and use either its Manager Tools or the corresponding hr patterns commands before running the instantiated workflow.

Supervised multi-Actor live panels

Use the concrete assets/orchestrations/multi-actor-live-report.yaml.template Workflow only when the user wants three stable, independently grounded panels for evidence research, skeptical analysis, and a screenshot-ready publication draft. It explicitly declares digest-pinned Surface views, report_surface_state, a three-Actor join, and await_command, so all three Actors remain addressable after their first round.

Choose exactly three Actors when each panel remains useful by itself, each has a non-overlapping responsibility, and the user benefits from later per-panel follow-ups. Share one source identity and evidence boundary. Parallelize only independent work. When analysis or publication must consume research output, author explicit data edges or structured handoffs instead of using the bundled parallel template unchanged. Use one Manager-owned Block for a simple answer or single report, and never add Actors merely to make the task look sophisticated.

Inside the Manager Agent, start it with start_supervised_dag and the exact yamlPath; pass the user's full objective as prompt and an available runtime profile only when one is required. Do not substitute the abstract orchestrator-workers pattern: that pattern performs dynamic fan-out and verification but intentionally has no live Surface or follow-up contract.

Read the full file on GitHub · 441 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 13d ago First seen · 441 lines · 153 tokens per session scan A f9ce6c176a34

Subscribe to this mod's changes

homerail-dag-ops is a skill published in the GitHub repository xiaotianfotos/homerail (951 stars, last pushed today), licensed MIT. It adds 153 tokens to every session and 4,248 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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