ao-workflow-runner

ao-workflow-runner is a skill for Claude Code, Codex from jnMetaCode/agency-orchestrator. It costs 34 tokens per session (647 once invoked), scanned A, original, Apache-2.0.

A workflow engine that reads YAML files and runs tasks assigned to different named roles. YAML is a text format for describing structured settings and steps.

In plain words
What is it for?
Running YAML workflows, coordinating role-based reviews or tasks, and passing results from one step to later steps.
Why use it?
It turns a multi-person or multi-agent process into ordered steps, including required inputs, dependencies, conditions, and repeated work.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Running YAML workflows, coordinating role-based reviews or tasks, and passing results from one step to later steps.

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Install with agentmods
npx agentmods add skills/jnmetacode/agency-orchestrator/deerflow
About the project

jnMetaCode/agency-orchestrator is a workflow system that lets people assemble teams of specialized AI roles from a natural-language request and run them against defined tasks and acceptance criteria. It is intended for individuals who want AI collaborators to produce research, content, products or other deliverables through web, desktop, Docker or command-line interfaces. The catalogue add-ons configure the agent roles and workflows used by the orchestrator.

jnMetaCode/agency-orchestrator · 2,217 stars · on GitHub · ao.aiolaola.com

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 jnMetaCode/agency-orchestrator --skill deerflow
Clone the repo
git clone --depth 1 https://github.com/jnMetaCode/agency-orchestrator

Made for: Claude Code, 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 ao-workflow-runner

README.md
[![agentmods](https://agentmods.dev/badge/skills/jnmetacode/agency-orchestrator/deerflow/github.svg)](https://agentmods.dev/skills/jnmetacode/agency-orchestrator/deerflow)
Your own site
<a href="https://agentmods.dev/skills/jnmetacode/agency-orchestrator/deerflow"><img src="https://agentmods.dev/badge/skills/jnmetacode/agency-orchestrator/deerflow/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 ao-workflow-runner

Your own site · 80×15
<a href="https://agentmods.dev/skills/jnmetacode/agency-orchestrator/deerflow"><img src="https://agentmods.dev/badge/skills/jnmetacode/agency-orchestrator/deerflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 647 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00034 $0.00647
Opus 5 $0.00017 $0.00324
Sonnet 5 $0.00007 $0.00129
Haiku 4.5 $0.00003 $0.00065

Measured 10d ago against content hash 25ff9a88b380, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ao-workflow-runner 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 10d 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.

integrations/deerflow/SKILL.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multi-Role Workflow Runner

When the user asks to run a workflow (YAML file) or a multi-role collaboration task, follow these steps:

1. Parse Workflow

Read the specified YAML file. Extract name, inputs, steps, depends_on, conditions, and loops.

2. Collect Inputs

  • required: true inputs must be provided by the user
  • Optional inputs with default use the default value
  • Optional inputs without default are set to empty string

3. Build Execution Order

Topological sort by depends_on. Steps without dependencies belong to the same level and can run in parallel.

4. Execute Steps

For each step:

  1. Read agency-agents-zh/{role}.md (search order: YAML's agents_dir → ./agency-agents-zh/ → ../agency-agents-zh/ → node_modules/agency-agents-zh/)
  2. Extract all markdown content after the frontmatter (---) as the role personality
  3. Replace {{variables}} in the task with context values (from inputs or previous step outputs)
  4. Evaluate conditions: if condition is set, evaluate it. Skip the step if the condition is not met. Operators: contains, equals, not_contains, not_equals
  5. Fully embody the role — use that role's expertise, frameworks, and communication style. Output should be substantive.
  6. Store the step's output text into the context variable (if step has an output field)
  7. Check loops: if loop is set and exit_condition is not met, jump back to loop.back_to step (max: loop.max_iterations rounds)

Label each step: ### Step N/Total: step_id (Role Name)

5. Save Results

Save all outputs to files:

ao-output/{workflow-name}-{date}/
├── steps/
│   ├── 1-{step_id}.md
│   └── ...
├── summary.md          # Final step's full output
└── metadata.json       # Step states, timing, token counts

6. Suggest Iteration

After completion, always tell the user:

To improve a specific step, ask me to re-run from that step. I'll reuse all upstream outputs. For CLI: ao run <workflow> --resume last --from <step-id>

Read the full file on GitHub · 56 lines

Files

What ships with it

1 file 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. 10d ago First seen · 56 lines · 34 tokens per session scan A 25ff9a88b380

Subscribe to this mod's changes

ao-workflow-runner is a skill published in the GitHub repository jnMetaCode/agency-orchestrator (2,217 stars, last pushed 3d ago), licensed Apache-2.0. It adds 34 tokens to every session and 647 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 2026-08-30.

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