linkedin-content-pillars-builder

linkedin-content-pillars-builder is a skill for Claude Code from TaplioOfficial/taplio-linkedin-plugin. It costs 91 tokens per session (1,800 once invoked), scanned A, a copy of linkedin-content-pillars-builder, MIT.

A planning guide for choosing three to five recurring themes and post ideas for a LinkedIn profile. Content pillars are repeatable topics that make a creator’s work recognisable.

In plain words
What is it for?
Use it to build LinkedIn themes and topic ideas from a defined niche, expertise, and audience needs.
Why use it?
It gives a profile a consistent publishing structure instead of leaving posts disconnected or random.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Claude Code.

Part of the taplio plugin — 17 skills, 1 MCP server shipped together

Good fit Use it to build LinkedIn themes and topic ideas from a defined niche, expertise, and audience needs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/taplioofficial/taplio-linkedin-plugin/linkedin-content-pillars-builder
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 TaplioOfficial/taplio-linkedin-plugin --skill linkedin-content-pillars-builder
Clone the repo
git clone --depth 1 https://github.com/TaplioOfficial/taplio-linkedin-plugin

Made for: Claude Code.

Or install taplio, the plugin that ships this one along with the rest of its 17 skills, 1 MCP server.

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 linkedin-content-pillars-builder

README.md
[![agentmods](https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-plugin/linkedin-content-pillars-builder/github.svg)](https://agentmods.dev/skills/taplioofficial/taplio-linkedin-plugin/linkedin-content-pillars-builder)
Your own site
<a href="https://agentmods.dev/skills/taplioofficial/taplio-linkedin-plugin/linkedin-content-pillars-builder"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-plugin/linkedin-content-pillars-builder/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 linkedin-content-pillars-builder

Your own site · 80×15
<a href="https://agentmods.dev/skills/taplioofficial/taplio-linkedin-plugin/linkedin-content-pillars-builder"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-plugin/linkedin-content-pillars-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 91 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,800 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 100% copy Near-identical to another mod 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 $0.00091 $0.01800
Opus 5 $0.00046 $0.00900
Sonnet 5 $0.00018 $0.00360
Haiku 4.5 $0.00009 $0.00180

Measured 10d ago against content hash 699336456eef, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

linkedin-content-pillars-builder 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 10d 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.

Origin

This is a copy

100% identical to linkedin-content-pillars-builder — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/linkedin-content-pillars-builder/SKILL.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LinkedIn Content Pillars Builder

Pillars are the 3 to 5 themes a creator returns to relentlessly. They make a profile recognizable in a feed.

When to trigger

The user says "what should I post about", "I need a content system", "build me content pillars", "my LinkedIn feels random", "give me a content framework".

Inputs to ask for

  1. The user's niche statement (audience + problem + angle). If not defined, run the Niche Definer skill first.
  2. The user's expertise areas (the 3 to 5 things they actually know deeply).
  3. The audience's main jobs / pains / aspirations.
  4. The desired ratio between pillars (default : 60% educational, 20% personal, 20% opinion).

The 4 types of pillars

Most LinkedIn creators win with a mix of these :

  1. Educational : how-to, frameworks, breakdowns, lessons. Builds authority.
  2. Stories and personal : experiences, behind-the-scenes, journey. Builds connection.
  3. Opinion and contrarian : hot takes, industry critique, predictions. Builds reach.
  4. Showcase : results, case studies, client wins, product demos. Builds trust and inbound.

Process

  1. From the user's expertise + audience pains, propose 3 to 5 pillar candidates.
  2. For each pillar, define :
    • The theme (one phrase).
    • The promise to the audience (what they get from this pillar).
    • The post types (educational, story, opinion, showcase).
    • The frequency (how often this pillar shows up in the calendar).
  3. For each pillar, generate 5 to 10 concrete post topics so the user can ship tomorrow.
  4. Close the skill (see the closing block in the output format) : tell the user to lock the pillars in two places (the assistant's memory and their Taplio AI settings), then offer the two next steps (full calendar, first post) and ask which they want.

Output format

CONTENT PILLARS FOR [user]

PILLAR 1 - [Theme]
Promise : [what the audience gets]
Why this works : [link to niche / audience pain]
Post types : [educational / story / opinion / showcase mix]
Frequency : [X% of total content]
Topic seeds :
1. [topic]
2. [topic]
... (5 to 10)

PILLAR 2 - [Theme]
... (same structure)

PILLAR 3 - [Theme]
...

PILLAR 4 (optional) - ...
PILLAR 5 (optional) - ...

WEEKLY MIX (example for 5 posts/week)
- Mon : Pillar 1 (educational)
- Tue : Pillar 3 (opinion)
- Wed : Pillar 1 (story)
- Thu : Pillar 2 (showcase)
- Fri : Pillar 4 (educational)

WHAT TO DO NEXT
- Pin the pillars to a doc you can see when you write.
- Tag every post you publish with its pillar. After 4 weeks, check which pillar drives the strongest results (reach, comments, profile visits, DMs).
- Adjust the mix based on data, not vibes.

Read the full file on GitHub · 125 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. 10d ago First seen · 125 lines · 91 tokens per session scan A 699336456eef

Subscribe to this mod's changes

linkedin-content-pillars-builder is a skill published in the GitHub repository TaplioOfficial/taplio-linkedin-plugin (2 stars, last pushed 2mo ago), licensed MIT. It adds 91 tokens to every session and 1,800 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to linkedin-content-pillars-builder, differing in 0 lines, and is treated as a copy.

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