batch-orchestrator

batch-orchestrator is an agent for Claude Code from teachskillofskills-ai/ContentForge-techshu. It costs 25 tokens per session (3,954 once invoked), scanned A, a copy of batch-orchestrator, MIT.

A queue manager for producing multiple pieces of content through the same set of steps and quality checks. It handles one piece at a time and records progress.

In plain words
What is it for?
Use it to process a list of content requirements, order them by priority, track each item's status, handle errors, and create a batch report.
Why use it?
It lets an interrupted batch continue from the last completed piece and step instead of starting over, while keeping the same review standards for every item.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths.

Part of the contentforge plugin — 22 skills, 9 commands, 13 agents shipped together

Good fit Use it to process a list of content requirements, order them by priority, track each item's status, handle errors, and create a batch report.

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Install with agentmods
npx agentmods add agents/teachskillofskills-ai/contentforge-techshu/09-batch-orchestrator
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.

Clone the repo
git clone --depth 1 https://github.com/teachskillofskills-ai/ContentForge-techshu

Made for: Claude Code.

Or install contentforge, the plugin that ships this one along with the rest of its 22 skills, 9 commands, 13 agents.

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 batch-orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/agents/teachskillofskills-ai/contentforge-techshu/09-batch-orchestrator/github.svg)](https://agentmods.dev/agents/teachskillofskills-ai/contentforge-techshu/09-batch-orchestrator)
Your own site
<a href="https://agentmods.dev/agents/teachskillofskills-ai/contentforge-techshu/09-batch-orchestrator"><img src="https://agentmods.dev/badge/agents/teachskillofskills-ai/contentforge-techshu/09-batch-orchestrator/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 batch-orchestrator

Your own site · 80×15
<a href="https://agentmods.dev/agents/teachskillofskills-ai/contentforge-techshu/09-batch-orchestrator"><img src="https://agentmods.dev/badge/agents/teachskillofskills-ai/contentforge-techshu/09-batch-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 25 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,954 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.
Origin 100% copy Near-identical to another mod 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 $0.00025 $0.03954
Opus 5 $0.00013 $0.01977
Sonnet 5 $0.00005 $0.00791
Haiku 4.5 $0.00003 $0.00395

Measured 8d ago against content hash 3e6f2a68d35e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

batch-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 8d 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.

Origin

This is a copy

100% identical to batch-orchestrator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

agents/09-batch-orchestrator.md · 330 lines

How it starts

The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent: Batch Orchestrator

Purpose: Process multiple ContentForge requirements as a sequential, checkpointed queue — one piece at a time, each piece running the full 10-phase pipeline (plus Step 0.5) with all 10 quality gates. Manage intake, priority ordering, per-piece status, error handling, and batch reporting.

Trigger: /contentforge:batch-process


Your Role

You are the Batch Orchestrator Agent. You maximize throughput honestly: pieces run one at a time, but every piece is checkpointed per phase, so an interrupted batch resumes from the exact piece and phase where it stopped instead of restarting. You never trade away quality gates for speed — every piece in the batch must meet the same standards as a single-piece run.

Execution model (important):

  • One piece at a time. Each piece = ONE Task call that runs the full pipeline Execution Protocol defined in skills/contentforge/SKILL.md (Step 0 init → Step 0.5 title → Phases 1–8 with orchestrator-verified gates and per-phase checkpoints).
  • No concurrency. Do not claim or attempt parallel pipelines: shared per-brand state, API rate limits, and context limits make concurrent in-session pipelines unsafe.
  • Batch pieces must be non-interactive. Every queued requirement must carry a title (passed as the --title bypass) or the pipeline will stall waiting for user title selection. If a requirement has no title, use its title column verbatim as the confirmed title.

Core Responsibilities

1. Queue Management

  • Load requirements from the brand's configured tracking backend (local JSON by default, Google Sheets, or Airtable)
  • Validate each requirement (required fields, brand exists, content type supported)
  • Build a priority-sorted execution queue

2. Sequential Execution Control

  • Run the queue front-to-back, one full pipeline per piece
  • After each piece completes (or fails), update the tracking backend and redraw the status table
  • Resume support: skip pieces whose checkpoint run is already completed; resume a piece whose run is in_progress via its checkpoint artifacts

Read the full file on GitHub · 330 lines

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. 8d ago First seen · 330 lines · 25 tokens per session scan A 3e6f2a68d35e

Subscribe to this mod's changes

batch-orchestrator is an agent published in the GitHub repository teachskillofskills-ai/ContentForge-techshu (1 stars, last pushed 19d ago), licensed MIT. It adds 25 tokens to every session and 3,954 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to batch-orchestrator, differing in 0 lines, and is treated as a copy.

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