Content Engine

• Source: Part of The Content Engine suite, seven skills built from the one agent per task workflow Mark Fershteyn described on the GTM AI Podcast with Coach K. Published as received.
• Frameworks applied: One agent per task pipeline, file handoff between steps, dated run folders, learnings.md as a growing rule set

Most content prompts do everything in one pass, so when the output is wrong there is nothing to fix. Splitting the work into six files means you can see exactly which step failed and rerun only that one.

Known weakness, published as found: It depends on the other six skills being installed. Run it without them and it has nothing to call.

1. 1.Copy the SKILL.md text below, or download the raw file.
2. 2.Create a folder named exactly content-engine in your agent's skills directory.
3. 3.Save the file inside that folder as SKILL.md.
4. 4.Ask the agent one of the trigger requests below.
5. 5.Check the output against what you already know before it leaves your desk.

• run the content engine on this topic
• turn this idea into a LinkedIn post, an X thread, and a newsletter section
• take this from idea to finished content

• just write me five hooks
• only edit this paragraph

---
name: content-engine
description: Runs the full content pipeline on one topic by calling six single-job skills in order (interview, draft, edit, hooks, repurpose, retro) and passing files between them. Use when the user says "run the content engine," "content engine on [topic]," "turn this idea into posts," "take this from idea to LinkedIn," "make content from this," "full content run," or wants one idea turned into finished posts for multiple channels. For a single step only (just hooks, just editing), use that step's skill directly.
---

# Content Engine (Orchestrator)

One job: run the six content skills in order and hand each one the file the last one produced.
This skill writes no content itself. Each step belongs to its own skill so you always know which one to fix.

Built from the one-agent-per-task workflow Mark Fershteyn showed on the GTM AI Podcast with Coach K.

## The pipeline

| Step | Skill | Reads | Writes |
|---|---|---|---|
| 1 | content-interviewer | topic from user | `interview.md` |
| 2 | content-drafter | `interview.md` | `draft.md` |
| 3 | content-editor | `draft.md` | `edited.md` |
| 4 | hook-writer | `edited.md` | `hooks.md` |
| 5 | content-repurposer | `edited.md`, `hooks.md` | `repurposed.md` |
| 6 | content-retro | all of the above + user feedback | appends to `learnings.md` |

All run files live in `content-runs/YYYY-MM-DD-topic-slug/`.
Shared files live in the workspace root: `voice/` (writing samples) and `learnings.md` (rules from past retros).

## STEP 0 (REQUIRED): Set up the run

1. Confirm the topic in one line. If the user gave no topic, ask: "What's the topic, and who is it for?" Do not proceed without a topic.
2. Create `content-runs/YYYY-MM-DD-topic-slug/`. Use today's date and a 2 to 5 word slug.
3. Check for `voice/`. If missing or holding fewer than 5 files, tell the user once: "No voice samples yet. Drop 10 or more of your best posts into `voice/` and I'll match them. Running with defaults for now." Then continue.
4. Check for `learnings.md`. If it exists, tell the user how many rules it holds.

## STEP 1 to 6 (REQUIRED): Run each skill in order

For each step:
- Load that step's skill and follow it exactly.
- Confirm its output file exists and passed that skill's check before starting the next step.
- If a step fails its check twice, stop and show the user what failed. Do not push a weak file downstream.

Between steps, give the user a one-line status: "Interview done (12 questions, 5 hard details). Drafting now."

The user can stop or skip at any point. If they say "skip the interview, here are my notes," save their notes as `interview.md` and start at Step 2.

## Running as separate agents (Claude Code)

If subagents are available, run Steps 2 to 5 each in a fresh subagent that receives only its input files and its skill. This keeps one job from bleeding into another. Steps 1 and 6 need live back-and-forth with the user, so run those in the main session.

## Done looks like

A run folder containing all five files, `learnings.md` updated, and a final message to the user:

```
Run complete: content-runs/2026-09-23-one-agent-rule/
- Edited piece: 412 words (cut 31% from draft)
- Top hook (score 27/30): "Your AI agent is bad because it has six jobs."
- Ready to post: LinkedIn, X thread (7 posts), newsletter section, 45-sec video script
- 2 new rules saved to learnings.md
```

## Edge cases

- **User pastes a finished draft:** save it as `draft.md` and start at Step 3.
- **User wants one channel only:** run Steps 1 to 4, then tell the repurposer which channel.
- **Topic too broad** ("AI in sales"): the interviewer narrows it. Do not start drafting on a broad topic.
- **Expect about four full runs** with honest retro feedback before output is consistently great. Plan roughly 30 minutes of feedback total. The results hold every run after.

What does the Content Engine skill do?

The orchestrator. Writes no content itself. Confirms the topic, creates a dated run folder, then hands each step the file the last one produced: interview.md, draft.md, edited.md, hooks.md, repurposed.md, and a retro that appends rules to learnings.md.

Where does the Content Engine skill come from?

Part of The Content Engine suite, seven skills built from the one agent per task workflow Mark Fershteyn described on the GTM AI Podcast with Coach K. Published as received.. It was written by The Revenue AI Report against a 12 criterion quality rubric and graded in an independent scoring pass.

Why was the Content Engine skill chosen for this library?

Most content prompts do everything in one pass, so when the output is wrong there is nothing to fix. Splitting the work into six files means you can see exactly which step failed and rerun only that one.

When should the Content Engine skill not be used?

Do not use it for: just write me five hooks Or: only edit this paragraph

How do I install the Content Engine SKILL.md file?

Download the file, create a folder named exactly content-engine inside your agent's skills directory, and save the file inside it as SKILL.md. The agent loads it when a request matches the description.