linkedin-comment-strategy

linkedin-comment-strategy is a skill for Claude Code, Codex from WingedGuardian/GENesis-AGI. It costs 86 tokens per session (1,230 once invoked), scanned A, original, MIT.

A guide for writing useful comments on LinkedIn posts, a professional social-networking site. Comments should add expertise, information, or a relevant perspective instead of only expressing approval.

In plain words
What is it for?
Use it to respond to a LinkedIn post, engage with valuable posts in your network, or write a comment that encourages a real conversation. It supports comments that extend an idea, share experience, or add nuance.
Why use it?
It helps avoid generic comments that add little to a discussion. It also uses the writer’s preferred voice and checks the comment against guidance for professional LinkedIn writing.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to respond to a LinkedIn post, engage with valuable posts in your network, or write a comment that encourages a real conversation. It supports comments that extend an idea, share experience, or add nuance.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wingedguardian/genesis-agi/linkedin-comment-strategy
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 WingedGuardian/GENesis-AGI --skill linkedin-comment-strategy
Clone the repo
git clone --depth 1 https://github.com/WingedGuardian/GENesis-AGI

Made for: Claude Code, Codex.

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-comment-strategy

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/wingedguardian/genesis-agi/linkedin-comment-strategy"><img src="https://agentmods.dev/badge/skills/wingedguardian/genesis-agi/linkedin-comment-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,230 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00086 $0.01230
Opus 5 $0.00043 $0.00615
Sonnet 5 $0.00017 $0.00246
Haiku 4.5 $0.00009 $0.00123

Measured 10d ago against content hash 07109f9d7e48, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

linkedin-comment-strategy 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.

src/genesis/skills/linkedin-comment-strategy/SKILL.md · 142 lines

How it starts

The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LinkedIn Comment Strategy

Purpose

Write LinkedIn comments that build genuine professional visibility — not generic "Great post!" noise. Every comment should demonstrate expertise, add value to the conversation, or make the author want to respond. Comments are the highest-ROI LinkedIn activity for building network presence.

Voice Loading

Before writing comments, load the user's voice via voice-master's overlay resolution:

  1. Read ../voice-master/SKILL.md and follow its User Calibration Overlay section to load exemplars and voice-dimensions from the out-of-repo overlay (or template fallback with warning if no overlay).
  2. This skill's medium is social. Select social-medium exemplars from whatever voice-master loads.
  3. Read ../voice-master/references/anti-slop.md — apply the Universal and Professional / LinkedIn sections.

If no overlay is present, voice-master falls back to generic voice guidance and warns — note this in your output.

Comments follow the same voice rules as posts but in compressed form.

Comment Types

1. Add-Value Comment

Extend the post's point with additional insight, a related experience, or a nuance the author didn't cover.

When to use: The post makes a good point that you can genuinely build on. Length: 2-4 sentences. Example pattern: "[Specific agreement with a detail]. In my experience with [specific context], [additional insight]. [Optional: question or implication]."

2. Respectful Challenge

Disagree with or complicate the post's thesis — with reasoning, not contrarianism.

When to use: The post oversimplifies something or misses a key angle. Length: 3-5 sentences. Example pattern: "[Acknowledge the valid part]. Where I'd push back is [specific point] because [evidence/experience]. [What this changes about the conclusion]."

3. Experience Share

Contribute a relevant personal experience that illustrates or complicates the post's point.

When to use: The post resonates with something you've lived through. Length: 3-6 sentences. Example pattern: "[Brief connection to the post]. When I was [specific situation], [what happened]. [What you learned or how it relates]."

Read the full file on GitHub · 142 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 · 142 lines · 86 tokens per session scan A 07109f9d7e48

Subscribe to this mod's changes

linkedin-comment-strategy is a skill published in the GitHub repository WingedGuardian/GENesis-AGI (96 stars, last pushed today), licensed MIT. It adds 86 tokens to every session and 1,230 once invoked, about $0.0004 per session on Opus 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 2026-08-30.

Related

Other skills, from other repositories

search

Unified academic paper search, citation chains, paper download (arXiv LaTeX/PDF, Sci-Hub), figure extraction from papers, LaTeX source reading, BibTeX fetching, web search, and browser automation for Cloudflare-protected sites (PRL, Science, Nature, Google Scholar).

Muuuun/luxas · 0 tokens

qec-construct

Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T). Applies whenever the project goal is a new or better code/construction — INCLUDING search-phrased goals ("find codes beating X"), where the construct-loop (propose algebraic rule → qverify → debug) is the…

Muuuun/luxas · 148 tokens

figure

Hybrid figure pipeline (Nano Banana raster + rembg background removal + TikZ vector assembly). Includes a TikZ template library covering quantum circuits (quantikz), Feynman diagrams (tikz-feynman), circuits (circuitikz), molecules (chemfig), 2D/3D plots (pgfplots), energy-level diagrams, phase-space trajectories…

Muuuun/luxas · 104 tokens

memory

Cross-project research memory. Deep-dive past projects' notes, record corrections, and save cross-project insights across all Luxas research projects.

Muuuun/luxas · 30 tokens

paper-figures

Extract figures from downloaded papers and include them in survey/review reports. Use when the report covers other groups' work and benefits from their architecture diagrams, experimental plots, or system schematics. Your brain prompt supplies the absolute path to the extract-figures script as {{EXTRACTFIGURES}} — use…

Muuuun/luxas · 79 tokens

compute-methods

Environment-verified friction sheets for field-standard computational tools (Rydberg pair interactions, QEC circuits, qLDPC decoding, code distance, atom dynamics, optics, quantum chemistry). Each sheet lists the tools the field actually uses, the first-use frictions that make agents wrongly abandon them, and one-line…

Muuuun/luxas · 113 tokens