linkedin-content

$npx mdskill add alirezarezvani/claude-skills/linkedin-content

The post is not the deliverable; the specific thing only this person can say is. The scripts handle format choice, mechanical faults, and de-duplication. The interesting part — what actually happened and what it cost — comes from the user, and cannot be generated.

SKILL.md

.github/skills/linkedin-contentView on GitHub ↗
---
name: linkedin-content
description: "Write, edit or review a LinkedIn post: story, how-to, carousel, video script or poll. Use whenever the user wants a LinkedIn post, asks if their draft is good, or wants a blog or talk turned into posts."
license: MIT
metadata:
  version: 1.0.0
  author: Alireza Rezvani
  category: marketing
  updated: 2026-08-25
---

# LinkedIn Content — format, draft, lint

The post is not the deliverable; the specific thing only this person can say is. The scripts
handle format choice, mechanical faults, and de-duplication. The interesting part — what
actually happened and what it cost — comes from the user, and cannot be generated.

## Workflow

**1. Check the brief exists.** If there is no positioning brief, offer `linkedin-strategy`
first as a question. Posts without pillars are noise. Never chain silently.

**2. Pick the format from the material, not from fashion.**

```bash
python3 scripts/format_picker.py --goal authority --material data --material tutorial \
  --minutes 120 --output human
```

Exit 0 recommends / 2 asks when the top two are within a point (tie-break on which one they
would enjoy making — the one they repeat beats the one that scores higher once) / 3 no fit,
go get material. It refuses video with no camera and no footage, and a poll with no real
decision behind it.

**3. Draft.** Interview for specifics before writing a line: the number, the mistake, the
sentence someone said. Then write to the fold — **the first ~140 characters are the whole
post for most readers**, and a sentence must complete inside them.

**4. Lint before it ships.**

```bash
python3 scripts/post_linter.py --input draft.md --has-image --output human
```

Exit 0 SHIP / 2 REVISE (or any blocking finding) / 3 REWRITE. Blocking findings have named
consequences: over the 3,000-character cap; engagement bait, named as demoted content in the
Professional Community Policies; Unicode pseudo-bold, which screen readers announce as
mathematical symbols and search does not index as words. Two passes is normal; the stop
condition is exit 0 or a stated decision to accept a warning.

**5. Repurposing.** Split a source and keep the ledger — it prevents the specific recurring
failure of the same idea going out three times over eight months. Commit it alongside the
source; it is project state, not a cache. Every unit is source material, not a post: add the
sentence only the author can write — what it cost, or what they would do differently.

```bash
python3 scripts/repurpose_splitter.py --input talk.md --ledger .linkedin-ledger.json --output human
python3 scripts/repurpose_splitter.py --input talk.md --ledger .linkedin-ledger.json --record 2 --posted-on 2026-08-25
```

## Rules

- **Never fabricate a number, a client, a result, or a quote.** Not one, not as a placeholder.
- **Write to the mobile fold.** A sentence completes before character 140.
- **Links in the first comment**, and say so in the post.
- **No Unicode pseudo-bold, ever.** It is an accessibility failure, not a style choice.
- **Alt text on every image; captions on every video.** LinkedIn does not add them for you.
- **No engagement bait.** Ask the question the post actually earned.
- **The author reads every line before it ships.** They are the author of record.

## Scripts

| Script | Role |
|---|---|
| [`scripts/post_linter.py`](scripts/post_linter.py) | 0-100 across mechanics / hook / integrity / accessibility; blocking findings for the cap, bait, and pseudo-bold. |
| [`scripts/format_picker.py`](scripts/format_picker.py) | Ranks nine native formats against goal, material, and minutes; refuses camera-less video and decision-less polls. |
| [`scripts/repurpose_splitter.py`](scripts/repurpose_splitter.py) | Splits a source into standalone units, scores them, and skips anything already in the reuse ledger. |

## References and assets

- [`references/hook_and_fold_mechanics.md`](references/hook_and_fold_mechanics.md) — the first 140 characters, and the openers to delete on sight (7 sources)
- [`references/post_formats_canon.md`](references/post_formats_canon.md) — what each native format is good at, and the carousel trap (7 sources)
- [`references/repurposing_discipline.md`](references/repurposing_discipline.md) — standalone units, the reuse ledger, source types and their risks (7 sources)
- [`references/accessibility_and_inclusion.md`](references/accessibility_and_inclusion.md) — pseudo-bold, alt text, captions, and why they are blocking (7 sources)

- [`assets/post_templates.md`](assets/post_templates.md) — five worked post shapes with the hook already doing its job
- [`assets/example_post.md`](assets/example_post.md) — a post that passes the linter, annotated

## Distinct from

- **`linkedin-strategy`** — decides what the posts are about. This writes them.
- **`linkedin-engagement`** — comments and DMs. A comment is a different craft with a
  different budget; it lives there.
- **`marketing-skill/copywriting` / `content-humanizer`** — general copy and de-AI passes.
  Reach for those for tone; this one owns LinkedIn's mechanics and its accessibility floor.

---

**Version:** 1.0.0

More from alirezarezvani/claude-skills

SkillDescription
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aeoUse when content should be cited by ChatGPT, Perplexity, Claude or Gemini (answer engine optimization), before rewriting it. Scores E-E-A-T and structure with aeo_audit.py, rewrites with aeo_optimizer.py and logs citations with citation_tracker.py.
agent-decision-receiptsUse when an autonomous agent takes a side-effecting action (deploy, delete, pay, grant access) that may need proving later, or for EU AI Act Art. 12 record-keeping. Builds a tamper-evident signed receipt with build_action_manifest.py and verifies it.
agent-designerDesign multi-agent systems (supervisor, swarm, pipeline) and tool schemas; find bottlenecks in run logs. Use whenever agents split work or a run is slow or costly. Not for Claude Code workflow files (workflow-builder).
agent-harnessUse when an agent should drive a goal in one of this repo's domains to a verified close, before starting the work. Compiles the goal into a task plan with goal_compiler.py and runs it through loop_controller.py, which verifies each task, caps retries and escalates.
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