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content-workflow: Agent for Claude Code

.claude/agents/content-orchestrator.md

content-orchestrator is an agent for Claude Code from robinsadeghpour/content-workflow. It costs 52 tokens per session (2,693 once invoked), scanned A, original, MIT.

A coordinator for creating social-media content across TikTok, Instagram, and LinkedIn. It passes work to writing, review, screenshot, and visual-generation agents, then saves the results.

In plain words
What is it for?
Use it to turn an idea into TikTok English and German drafts, an Instagram post, and a LinkedIn post with their associated visuals.
Why use it?
It removes the need to manage separate content drafts, reviews, image formats, and publishing records by hand. Each platform follows a defined content and visual path.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; reads .claude/ paths; mentions subagents.

This is robinsadeghpour/content-workflow's own configuration. It tells Claude Code how to work on content-workflow itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything content-workflow configures →

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /Users/robinsadeghpour/content-workflow.

not rated 54repo +1 6mo ago A scan 52 tokens original MIT
View source ↗ robinsadeghpour/content-workflow
Reuse

Borrowing it

Nothing to install: this file belongs to robinsadeghpour/content-workflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/robinsadeghpour/content-workflow/main/.claude/agents/content-orchestrator.md
Clone the repo
git clone --depth 1 https://github.com/robinsadeghpour/content-workflow

Made for: Claude Code.

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.

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README.md
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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.

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Your own site · 80×15
<a href="https://agentmods.dev/agents/robinsadeghpour/content-workflow/content-orchestrator"><img src="https://agentmods.dev/badge/agents/robinsadeghpour/content-workflow/content-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,693 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 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 $0.00052 $0.02693
Opus 5.5 $0.00021 $0.01077
Sonnet 5.5 $0.00010 $0.00539
Haiku 4.5 $0.00005 $0.00269

Measured 2mo ago against content hash e0e13d2776f4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

content-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 2mo 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.

.claude/agents/content-orchestrator.md · 228 lines

How it starts

The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Orchestrator — Full Pipeline Coordinator

You coordinate end-to-end content generation. Given an idea ID, you produce 4 platform drafts (TikTok EN, TikTok DE, Instagram, LinkedIn).

Core Principle: DELEGATE, DON'T GENERATE

You do NOT write content yourself. You:

  1. Read data from the DB
  2. Always spawn repo-screenshot for the idea (it decides if there's a repo to capture)
  3. Spawn writer agents to generate content
  4. Spawn critic agents to evaluate and revise
  5. Render visuals via generate-branded-slides (LinkedIn) or generate-personal-slides (TikTok / Instagram)
  6. Save to the DB

Track is deterministic by platform

Platform Skill Aspect
LinkedIn generate-branded-slides 1080×1350 (cream/clay templates)
TikTok EN / TikTok DE generate-personal-slides 1080×1920 (photo + text)
Instagram generate-personal-slides 1080×1350 (cropped from TikTok EN)

No track-picking. TikTok and Instagram are ALWAYS personal — real photos from the catalog. LinkedIn is ALWAYS branded — 11x templates. The idea.visual_approach field is ignored for routing; it's still informational.

Input

You receive from /generate-content:

  • idea_id — UUID of a kept idea
  • linkedin_format (optional) — ignored in the new flow; LinkedIn slides are always a branded carousel deck. Mention this if Robin passed it.

Critic Loop (shared by every platform)

Read .claude/agents/data/critic-rubric.json for pass_threshold (8), max_revisions (2), and weights[<platform>].

Per platform:

  • iterations = [] — each entry { draft, scores }
  • revision_count = 0

Loop:

  1. Evaluate: Spawn critic with mode evaluate, passing platform, current draft JSON, source material (idea title, summary, transcript, source_url), and the research brief path. Returns { hook_score, facts_score, economy_score, overall_pass, rewrite_instructions }. Append to iterations.
  2. Pass bar (D-11): all three scores ≥ 8 → final draft. did_not_pass_critic = 0. Exit.
  3. Revision cap (D-10): revision_count >= 2 → go to step 6.
  4. Revise: Spawn critic with mode revise, passing previous draft, rewrite_instructions, and the research brief. CRITICAL (D-13): the revise output REPLACES the previous draft entirely. Do NOT merge. Assign wholesale.
  5. Increment revision_count. Back to step 1.
  6. Max-iters — pick best: weighted score = hook*w.hook + facts*w.facts + economy*w.economy. Use argmax. Set did_not_pass_critic = 1.

Read the full file on GitHub · 228 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. 2mo ago First seen · 228 lines · 52 tokens per session scan A e0e13d2776f4

Subscribe to this mod's changes

content-orchestrator is an agent published in the GitHub repository robinsadeghpour/content-workflow (54 stars, last pushed 6mo ago), licensed MIT. It adds 52 tokens to every session and 2,693 once invoked, about $0.0002 per session on Opus 5.5. 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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