content-orchestrator

content-orchestrator is a skill for Claude Code from spinningrachel/career-engine. It costs 26 tokens per session (901 once invoked), scanned A, original, MIT.

A set of rules for an agent that plans a varied mix of social-media content. It assigns posts to three formats based on whether they present a framework, an observation, or a procedure.

In plain words
What is it for?
It helps choose formats for batches of three to five posts, maintain a target mix, and handle cases where the available ideas do not support that mix.
Why use it?
A content calendar can become repetitive or unbalanced when every idea is presented the same way. These rules help select and distribute formats while removing duplicate ideas.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the career-engine plugin — 29 skills, 16 agents, 1 hook shipped together

Good fit It helps choose formats for batches of three to five posts, maintain a target mix, and handle cases where the available ideas do not support that mix.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/spinningrachel/career-engine/content-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.

Any agent
npx skills add spinningrachel/career-engine --skill content-orchestrator
Clone the repo
git clone --depth 1 https://github.com/spinningrachel/career-engine

Made for: Claude Code.

Or install career-engine, the plugin that ships this one along with the rest of its 29 skills, 16 agents, 1 hook.

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 content-orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/skills/spinningrachel/career-engine/content-orchestrator/github.svg)](https://agentmods.dev/skills/spinningrachel/career-engine/content-orchestrator)
Your own site
<a href="https://agentmods.dev/skills/spinningrachel/career-engine/content-orchestrator"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/content-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 content-orchestrator

Your own site · 80×15
<a href="https://agentmods.dev/skills/spinningrachel/career-engine/content-orchestrator"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/content-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 901 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 $0.00026 $0.00901
Opus 5 $0.00013 $0.00451
Sonnet 5 $0.00005 $0.00180
Haiku 4.5 $0.00003 $0.00090

Measured 9d ago against content hash 69d8475dbf3c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, 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 9d 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.

skills/content-orchestrator/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Orchestrator Skill

Format Mix

The target mix ensures the content calendar doesn't become monotone. A feed of all Format A posts is dense and exhausting; all Format C posts signals a lack of depth. The mix keeps variety visible to followers.

Target: ~50% Format A / ~30% Format B / ~20% Format C

This is a target, not a hard constraint. Apply it across a batch of 3–5 posts. For a batch of 3:

  • Ideal: 2A + 1B, or 1A + 1B + 1C
  • Acceptable: 2A + 1C, or 1A + 2B
  • Avoid: 3A (too dense), 3C (too thin), 2C + 1A (imbalanced)

For a batch of 5:

  • Ideal: 2A + 2B + 1C, or 3A + 1B + 1C
  • Avoid: 4A + 1C, or 3C + 2B

Format assignment by idea content:

  • Assign Format A when the idea has a repeatable model or framework with 2+ real proof points — check the idea's Summary and Raw Notes before assigning
  • Assign Format B when the idea is a sharp observation with one real example or scenario
  • Assign Format C when the idea is procedural, tool-specific, or step-by-step

If the mix of available ideas doesn't support the target (e.g., all ideas are Format A candidates), note this in the batch proposal and proceed with the available formats rather than force-assigning the wrong format.

Batch Selection Criteria

When selecting which ideas to include in a batch:

  1. Prefer ideas with fuller Raw Notes. An idea with detailed notes produces a better post than one with a bare title. The Summary and Raw Notes fields are the evidence — if they're thin, flag the idea as "needs development" rather than including it.

  2. Topic variety within a batch. Avoid two ideas from the same Topic Authority Area in the same batch. Readers see the whole batch over a few days — topic monotony is visible. Refer to ${CAREER_DATA}/references/voice-and-identity/linkedin-post-strategy.md for the authority areas.

  3. Category distribution. Don't run a batch of all LinkedIn Post category ideas if Content Framework or Personal Experience ideas are available — different categories produce different post textures.

Read the full file on GitHub · 68 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. 9d ago First seen · 68 lines · 26 tokens per session scan A 69d8475dbf3c

Subscribe to this mod's changes

content-orchestrator is a skill published in the GitHub repository spinningrachel/career-engine (4 stars, last pushed 28d ago), licensed MIT. It adds 26 tokens to every session and 901 once invoked, about $0.0001 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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