Content Editor

• 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: Three-pass edit, 20 to 40 percent cut target, lint_copy.py checks

The cut target and the script make the edit checkable. You can see the word count drop and the flag list clear instead of trusting a claim that it was tightened.

Known weakness, published as found: The script is a flag list, not a judge. It cannot tell a deliberate stylistic choice from a lazy one.

1. 1.Copy the SKILL.md text below, or download the raw file.
2. 2.Create a folder named exactly content-editor 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.

• edit this draft and cut the fluff
• make this sound less like AI
• tighten this up without losing the facts

• research this topic for me
• write the X thread version

---
name: content-editor
description: Cuts and sharpens a draft so it sounds like a person talking, then runs a script that flags em dashes, AI phrases, hedges, and long paragraphs. Use when the user says "edit this," "tighten this up," "cut this down," "make this sound less like AI," "punch this up," "clean up my draft," "edit draft.md," or when the content-engine runs Step 3. Does not write hooks or channel versions.
---

# Content Editor

One job: make the draft shorter, sharper, and human. Keep every fact.

## STEP 1 (REQUIRED): Load inputs

1. Read `draft.md` (or the text the user pasted).
2. Read `voice/` samples and `learnings.md` if present. Rules in `learnings.md` override this skill.
3. Save the original word count. You'll need it for the cut check.

## STEP 2 (REQUIRED): Three edit passes, in order

**Pass 1: Structure.** Does it open on the strongest fact? Is there exactly one idea? Move or cut anything that wanders.

**Pass 2: Line edit.** Read each sentence out loud in your head. Cut any sentence that adds no fact, step, or turn.
- Paragraphs: 1 to 3 sentences
- Swap abstract words for the concrete detail behind them
- Active voice ("we cut" over "was reduced")
- At most one hedge ("I think") in the whole piece
- Remove all source tags like `[Q4]`

**Pass 3: Voice match.** Compare against `voice/`. Match sentence length, openings, and word choice.

### Good/bad pairs

| Before | After |
|---|---|
| "In today's rapidly evolving landscape, sales teams are leveraging AI to drive efficiencies." | "Our SDRs cut research from 45 minutes to 8." |
| "This was a game-changer for our team. Truly transformative." | "We got 4 hours a week back per rep." |
| "It could potentially help some teams improve outcomes." | "It will help any team that researches accounts by hand." |

## STEP 3 (REQUIRED): Run the lint script

Save the edited text to `edited.md`, then run:

```bash
python scripts/lint_copy.py edited.md --before draft.md
```

The script checks: em and en dashes, banned AI phrases, "it's not X, it's Y" constructions, hedge count, paragraphs over 3 sentences, and percent cut from the draft.

Fix every FAIL. Re-run until it prints `RESULT: PASS`. Do not hand off a file that fails.

To add your own banned phrases, create `banned.txt` in the workspace root (one phrase per line). The script reads it automatically.

## Output: `edited.md`

The clean piece only. No notes, no tags. Then tell the user in one line: "Edited: 598 to 412 words (31% cut). Lint: PASS."

## Pass criteria

- Lint script prints PASS
- 20 to 40 percent shorter than the draft (the script warns outside this range)
- Every number and quote from the draft is still present unless the user approved cutting it

## Edge cases

- **Draft is already tight** (under 20% cut possible): cut what you can and note it. Do not pad.
- **User's voice uses dashes or long paragraphs on purpose:** add a rule to `learnings.md` and follow it.
- **No Python available:** run the checks from the script's lists by hand and report each one.

What does the Content Editor skill do?

Three passes in order: structure, line edit, then voice match against your own writing samples. Targets a 20 to 40 percent cut while keeping every fact, then runs lint_copy.py to flag em dashes, AI tells, hedges, and long paragraphs.

Where does the Content Editor 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 Editor skill chosen for this library?

The cut target and the script make the edit checkable. You can see the word count drop and the flag list clear instead of trusting a claim that it was tightened.

When should the Content Editor skill not be used?

Do not use it for: research this topic for me Or: write the X thread version

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

Download the file, create a folder named exactly content-editor 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.