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Editorial Ops

Community
gtmagents
editorial-ops

Use when planning multi-channel editorial calendars, enforcing publishing cadences, and coordinating distribution workflows across GTM teams.

Overview

Publishergtmagents
Repositorygtm-agents
Skill nameeditorial-ops
Stars
428
Forks
83
Bundled files
2
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by gtmagents on GitHub. Read the source before you install it.

Installation

Install the Editorial Ops AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/gtmagents/gtm-agents/tree/main/plugins/content-marketing/skills/editorial-ops
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/gtmagents/gtm-agents.git /tmp/gtm-agents
mkdir -p .claude/skills
cp -r /tmp/gtm-agents/plugins/content-marketing/skills/editorial-ops .claude/skills/editorial-ops
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Editorial Ops in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Editorial Ops on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Editorial Ops is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Editorial Operations Skill

When to Use

  • Building or refreshing quarterly editorial roadmaps tied to GTM objectives.
  • Translating thought-leadership pillars into weekly blog, newsletter, and social programming.
  • Auditing production capacity, approvals, and distribution SLAs to eliminate bottlenecks.

Framework

  1. North Star & Themes – lock the executive thesis and supporting pillars (see GTM Agents Marketing Director guidance @puerto/README.md#183-212).
  2. Cadence Grid – map channels (blog, podcast, webinar, newsletter, LinkedIn) vs. frequency, owner, and CTA.
  3. Production Swimlanes – ideation → outline → draft → edit → design → approvals → launch.
  4. Distribution Tree – primary asset → derivative snippets → paid boosts → lifecycle inserts.
  5. Measurement Layer – define KPI guardrails (reach, engagement, SQL influence, pipeline velocity) before content leaves drafting.

Workflow Checklist

  • Weekly Editorial Stand-up (30 min): review status board, unblock owners, confirm launches.
  • Content Readiness Criteria: complete brief, stakeholder quotes, sources cited, SEO target, CTA alignment.
  • Approval Paths: highlight who signs off (Content Strategist, Brand, Legal) and expected turnaround.
  • Escalation Matrix: Marketing Director + Project Manager contacts for scope or timeline changes.

Templates

  • Editorial Calendar: See assets/editorial_calendar_template.md for tracking content.
  • Distribution Brief: See assets/distribution_brief.md for launch checklists.
  • Post-Launch Debrief template capturing performance vs. guardrails, learnings, and follow-up actions.
  • Ops Dashboard view showing backlog aging, production velocity, and publication mix.

Tips

  • Treat every flagship asset like a mini campaign: pair the lifecycle-mapping blueprint (Plan → Build → QA → Launch → Inspect) with editorial checkpoints.
  • Partner with Marketing Analytics to instrument dashboards early; no asset ships without a measurement plan.
  • Keep a "Parking Lot" section for emergent ideas so high-priority launches retain focus.
  • Borrow GTM Agents's status packet format (see lifecycle-mapping skill) for weekly exec updates.

Tooling Hooks

  • Serena: patch CMS or marketing automation snippets safely during content QA.
  • Context7: fetch current GA4/HubSpot docs when defining measurement plans.
  • Sequential Thinking: reason through campaign narratives or backlog reprioritization.
  • Playwright: capture screenshots of new landing pages or gated assets before publishing.

Deliverables

  1. Quarterly editorial roadmap (themes, owners, launch dates).
  2. Weekly status packet summarizing highlights, KPIs, blockers, and next five actions.
  3. Distribution checklist signed by Marketing Director + Sales counterpart to ensure coverage.

Quality Gates

  • KPI guardrails documented pre-launch (reach %, CTR, SQL influence, retention impact).
  • Approval sign-offs stored with links/timestamps for audit trail.
  • Post-launch retro completed within 5 business days, feeding insights back into the backlog.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Editorial Ops AI skill do?

Use when planning multi-channel editorial calendars, enforcing publishing cadences, and coordinating distribution workflows across GTM teams.

Why use Editorial Ops on TypingMind?

Because you install it once and use it with any model. Editorial Ops is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Editorial Ops in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gtmagents/gtm-agents/tree/main/plugins/content-marketing/skills/editorial-ops. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Editorial Ops?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Editorial Ops?

As many as you like. As long as a model supports skills, you can use Editorial Ops with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Editorial Ops AI skill free?

Yes. It is published on GitHub by gtmagents under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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