share

share is a skill for Claude Code from SerhiiKorniienko/bullshit-detector. It costs 93 tokens per session (857 once invoked), scanned A, original, MIT.

A publishing tool that turns a finished fact-checking report or other analysis into posts tailored to different platforms. It can also create a visual carousel as PNG images and a PDF.

In plain words
What is it for?
Use it to create posts for X, LinkedIn, Facebook, Reddit, Hacker News, or a newsletter, and to render a report into slides for visual sharing.
Why use it?
The same report does not fit every platform's format, length, or link conventions. This prepares separate, ready-to-paste versions for the audiences and publishing channels you choose.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the bullshit-detector plugin — 7 skills, 1 agent shipped together

Good fit Use it to create posts for X, LinkedIn, Facebook, Reddit, Hacker News, or a newsletter, and to render a report into slides for visual sharing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/serhiikorniienko/bullshit-detector/share
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 SerhiiKorniienko/bullshit-detector --skill share
Clone the repo
git clone --depth 1 https://github.com/SerhiiKorniienko/bullshit-detector

Made for: Claude Code.

Or install bullshit-detector, the plugin that ships this one along with the rest of its 7 skills, 1 agent.

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 share

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/serhiikorniienko/bullshit-detector/share"><img src="https://agentmods.dev/badge/skills/serhiikorniienko/bullshit-detector/share.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 857 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 $0.00093 $0.00857
Opus 5 $0.00046 $0.00428
Sonnet 5 $0.00019 $0.00171
Haiku 4.5 $0.00009 $0.00086

Measured 12d ago against content hash 952544ca787e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

share 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/render_carousel.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.

skills/publishing/share/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

share

Take a finished report and produce platform-native content, ready to paste. Nothing generic: each platform gets its own format, length, and link etiquette.

Workflow

  1. Locate the report. A file the user points at, the report from this conversation, or — if there is none — offer to run the bullshit-detector skill first.
  2. Ask which platforms if not stated. Default set: X thread + LinkedIn post.
  3. Write the posts following the per-platform specs in PLATFORMS.md exactly — hooks, length limits, link placement. Output each as a separate fenced block the user can copy verbatim.
  4. Carousel (if requested or if the platform benefits): extract the report into a slides.json (schema below) and render:
uv run <this-skill-dir>/scripts/render_carousel.py slides.json -o carousel/

First run needs a one-time browser install: uv run --with playwright playwright install chromium. Output: slide-N.png (1080×1350, works on X, LinkedIn, Instagram) + carousel.pdf (LinkedIn document post).

slides.json schema

{
  "title": "Video/article title",
  "source": "Author · Platform · 1.16M views",
  "score": 5,
  "verdict_line": "Real tools, fantasy income math",
  "footer": "@their-handle · their-link (the sharer's, not the tool author's — see rules)",
  "slides": [
    { "type": "hook" },
    { "type": "claim", "n": "1/12", "claim": "Quoted or paraphrased claim, ≤200 chars",
      "verdict": "misleading", "evidence": "One-sentence reality, ≤160 chars" },
    { "type": "cta", "headline": "Run it on anything",
      "lines": ["the sharer's own links — ask, don't assume"] }
  ]
}

Verdicts: confirmed / plausible / misleading / false / unverifiable / not checked — the same six the report uses, and the renderer rejects anything else rather than guessing a colour. Pick 3–4 claim slides — the spiciest verdicts with the strongest evidence, not the first four. Hook and CTA slides bookend them.

A not checked claim renders, but think before using one: it carries no verdict and no evidence by definition, so it makes a weak slide and a reader may take the empty cell for a finding.

Read the full file on GitHub · 54 lines

Files

What ships with it

3 files 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. 12d ago First seen · 54 lines · 93 tokens per session scan A 952544ca787e

Subscribe to this mod's changes

share is a skill published in the GitHub repository SerhiiKorniienko/bullshit-detector (142 stars, last pushed 8d ago), licensed MIT. It adds 93 tokens to every session and 857 once invoked, about $0.0005 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.