social-media-scheduler

social-media-scheduler is a skill for Claude Code from Affitor/affiliate-skills. It costs 119 tokens per session (3,467 once invoked), scanned A, original, MIT.

A planner for creating a 30-day social-media calendar for affiliate marketing. Affiliate marketing means earning a commission when someone buys through your link.

In plain words
What is it for?
Use it to prepare platform-specific post text, hashtags, and suggested posting times for LinkedIn, X, Facebook, and Reddit.
Why use it?
It removes the need to decide every day what to publish and helps balance useful posts with product promotions.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Claude Code; built for openclaw; mentions Gemini CLI.

Part of the distribution-skills plugin — 4 skills shipped together

Good fit Use it to prepare platform-specific post text, hashtags, and suggested posting times for LinkedIn, X, Facebook, and Reddit.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/affitor/affiliate-skills/social-media-scheduler
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 Affitor/affiliate-skills --skill social-media-scheduler
Clone the repo
git clone --depth 1 https://github.com/Affitor/affiliate-skills

Made for: Claude Code.

Or install distribution-skills, the plugin that ships this one along with the rest of its 4 skills.

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 social-media-scheduler

README.md
[![agentmods](https://agentmods.dev/badge/skills/affitor/affiliate-skills/social-media-scheduler/github.svg)](https://agentmods.dev/skills/affitor/affiliate-skills/social-media-scheduler)
Your own site
<a href="https://agentmods.dev/skills/affitor/affiliate-skills/social-media-scheduler"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/social-media-scheduler/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 social-media-scheduler

Your own site · 80×15
<a href="https://agentmods.dev/skills/affitor/affiliate-skills/social-media-scheduler"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/social-media-scheduler.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,467 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 $0.00119 $0.03467
Opus 5 $0.00060 $0.01733
Sonnet 5 $0.00024 $0.00693
Haiku 4.5 $0.00012 $0.00347

Measured 13d ago against content hash 74559875a0b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

social-media-scheduler 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 13d 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

Copies of this mod

2 near-identical copies found in the catalogue:

skills/distribution/social-media-scheduler/SKILL.md · 305 lines

How it starts

The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Social Media Scheduler

Generate a complete 30-day social media content calendar with post copy, hashtags, and scheduling times for LinkedIn, X (Twitter), Facebook, and Reddit. Follows the 80/20 rule: 80% value and engagement content, 20% affiliate promotions. Every post is ready to copy-paste or load into a scheduling tool.

Stage

S5: Distribution — Social media is the top free traffic channel for affiliate marketers. This skill eliminates "what do I post today?" paralysis by giving you 30 days of content in one shot, optimized for each platform's algorithm and audience behavior.

When to Use

  • User wants a content plan for promoting an affiliate product over 30 days
  • User asks for a social media calendar, posting schedule, or content strategy
  • User wants platform-specific posts (LinkedIn professional angle, X casual, Reddit community-first)
  • User has an audience on one or more social platforms and wants consistent posting
  • Chaining from S1 (product research) — user found a product and now wants a social plan

Input Schema

product:
  name: string              # REQUIRED — product being promoted (e.g., "Semrush")
  affiliate_url: string     # REQUIRED — affiliate tracking link
  category: string          # OPTIONAL — e.g., "SEO tool", "AI writing tool"
  key_benefits: string[]    # OPTIONAL — top benefits. Inferred if not provided.
  price: string             # OPTIONAL — e.g., "starts at $119/mo"
  free_trial: boolean       # OPTIONAL — does the product have a free trial?

creator:
  niche: string             # REQUIRED — your content niche (e.g., "SEO for freelancers")
  audience: string          # REQUIRED — who follows you (e.g., "freelance SEO consultants")
  tone: string              # OPTIONAL — "professional" | "casual" | "educational" | "bold"
                            # Default: "educational"
  personal_story: string    # OPTIONAL — brief personal experience with the product

platforms:
  - string                  # REQUIRED — list of platforms: "linkedin" | "x" | "facebook" | "reddit"
                            # Default: ["linkedin", "x"]

calendar:
  start_date: string        # OPTIONAL — ISO date (e.g., "2026-04-01"). Default: next Monday.
  posts_per_week: number    # OPTIONAL — 3-7. Default: 5 (weekdays only)
  promotion_ratio: number   # OPTIONAL — % of posts that are affiliate promo. Default: 20

Read the full file on GitHub · 305 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 13d ago First seen · 305 lines · 119 tokens per session scan A 74559875a0b3

Subscribe to this mod's changes

social-media-scheduler is a skill published in the GitHub repository Affitor/affiliate-skills (658 stars, last pushed 7d ago), licensed MIT. It adds 119 tokens to every session and 3,467 once invoked, about $0.0006 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

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