dev-suite: Skill for Gemini CLI

.gemini/config/skills/linkedin/SKILL.md

linkedin is a skill for Gemini CLI from kk376/dev-suite. It costs 127 tokens per session (2,882 once invoked), scanned A, original, MIT.

A guide for managing LinkedIn profiles and posts, including technical or founder content. LinkedIn is a professional social network used for profiles, publishing, and career-related audiences.

In plain words
What is it for?
Use it to revise a LinkedIn headline or About section, create technical or founder posts, audit a profile, and plan a publishing workflow.
Why use it?
It gives a repeatable process for improving profile text, drafting posts, auditing content, and handling publishing decisions.

Skill for Gemini CLI

Written for Gemini CLI: installed under .gemini/.

This is kk376/dev-suite's own configuration. It tells Gemini CLI how to work on dev-suite itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything dev-suite configures →

Reuse

Borrowing it

Nothing to install: this file belongs to kk376/dev-suite. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/kk376/dev-suite/main/.gemini/config/skills/linkedin/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/kk376/dev-suite

Made for: Gemini CLI.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/kk376/dev-suite/linkedin/github.svg)](https://agentmods.dev/skills/kk376/dev-suite/linkedin)
Your own site
<a href="https://agentmods.dev/skills/kk376/dev-suite/linkedin"><img src="https://agentmods.dev/badge/skills/kk376/dev-suite/linkedin/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

Your own site · 80×15
<a href="https://agentmods.dev/skills/kk376/dev-suite/linkedin"><img src="https://agentmods.dev/badge/skills/kk376/dev-suite/linkedin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 127 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,882 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 original No closer match found 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 $0.00127 $0.02882
Opus 5.5 $0.00051 $0.01153
Sonnet 5.5 $0.00025 $0.00576
Haiku 4.5 $0.00013 $0.00288

Measured 1mo ago against content hash aa8efe49c5f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

linkedin 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 1mo ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/check_markdown_references.py, scripts/check_no_secrets.py, scripts/linkedin_tool.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.gemini/config/skills/linkedin/SKILL.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LinkedIn Profile Architecture, 2026 Feed Physics & Content Operations

A unified, production-grade standard for managing, auditing, and scaling a technical founder or developer's LinkedIn presence. Synthesizes the 9-Component Profile Conversion Engine, 2026 LinkedIn Feed & Algorithm Physics (derived from the 360Brew paper arXiv:2501.16450 and AuthoredUp empirical datasets), 20 Hook Formulas & 10 Founder Content Angles, Humanizer AI-Tell Elimination, Untrusted Scraped Content Prompt-Injection Defense, and a Three-Tier Publishing Pipeline.


The Master LinkedIn Content & Profile Lifecycle

Every profile revision, post draft, and engagement interaction follows a disciplined progression:

┌─────────────────────────────────────────────────────────────────────────────────────────┐
│                    THE LINKEDIN PROFILE & CONTENT ENGINEERING LIFECYCLE                 │
└─────────────────────────────────────────────────────────────────────────────────────────┘
                                           │
  1. Profile Architecture & Audit          ▼
     [9-Component Scorecard] ──────► [220-Char Headline] ────► [7-Step About (265-Char Fold)]
                                           │                                    │
                                           ├────────────────────────────────────┘
  2. Content Planning & Pillars            ▼
     [4 Founder Pillars] ──────────► [Weekly Editorial DAG] (Conviction / Public / Math / Proof)
                                           │
                                           ▼
                               [Hook Formula Selection] (F1–F20 + Angles A1–A10)
                                           │
  3. Draft Generation & Humanizer          ▼
     [Technical Draft] ────────────► [Humanizer De-Sloppify] ◄──► [AI-Tell & Vocabulary Purge]
                                           │                                 │
                                           │                                 ▼
                                           │                      [Emoji Density & Rhythm Gate]
                                           ▼                                 │
                                 [Algorithmic Heuristics] ◄──────────────────┘
                                           │ (Format Multiplier, 210-Char Mobile Fold, No-Links)
  4. Defensive Security & Approval         ▼
     [Untrusted Content Defense] ──► [Human User Approval Gate] (Fail-Closed, Zero Auto-Post)
                                           │
  5. Publishing & 90-Min Momentum          ▼
     [Tier 0: Copy-Paste] ─────────► [Tier 1: Publora API] ──► [Momentum Window (Replies < 90m)]

Read the full file on GitHub · 123 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. 1mo ago First seen · 123 lines · 127 tokens per session scan A aa8efe49c5f5

Subscribe to this mod's changes

linkedin is a skill published in the GitHub repository kk376/dev-suite (0 stars, last pushed 28d ago), licensed MIT. It adds 127 tokens to every session and 2,882 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-12.

Related

linkedin compared with skills from other repositories

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