selectedleafs-telegram

selectedleafs-telegram is a skill for Claude Code, Codex from wemwi/skill-library. It costs 189 tokens per session (7,548 once invoked), scanned A, original, no licence file.

A German-language playbook for running local Telegram city channels for selectedleafs. It defines post formats, message templates, emojis, pinned posts, launch steps, and content placeholders.

In plain words
What is it for?
Use it to plan channel launches and prepare Telegram posts for different cities.
Why use it?
It provides a consistent structure for creating and publishing channel content instead of deciding the format each time.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to plan channel launches and prepare Telegram posts for different cities.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wemwi/skill-library/selectedleafs-telegram
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 wemwi/skill-library --skill selectedleafs-telegram
Clone the repo
git clone --depth 1 https://github.com/wemwi/skill-library

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 selectedleafs-telegram

README.md
[![agentmods](https://agentmods.dev/badge/skills/wemwi/skill-library/selectedleafs-telegram/github.svg)](https://agentmods.dev/skills/wemwi/skill-library/selectedleafs-telegram)
Your own site
<a href="https://agentmods.dev/skills/wemwi/skill-library/selectedleafs-telegram"><img src="https://agentmods.dev/badge/skills/wemwi/skill-library/selectedleafs-telegram/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 selectedleafs-telegram

Your own site · 80×15
<a href="https://agentmods.dev/skills/wemwi/skill-library/selectedleafs-telegram"><img src="https://agentmods.dev/badge/skills/wemwi/skill-library/selectedleafs-telegram.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 189 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,548 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 unknown 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 $0.00189 $0.07548
Opus 5.5 $0.00076 $0.03019
Sonnet 5.5 $0.00038 $0.01510
Haiku 4.5 $0.00019 $0.00755

Measured 1mo ago against content hash 437e329f6be3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

selectedleafs-telegram 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.

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.

selectedleafs-telegram/SKILL.md · 318 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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 · 318 lines · 189 tokens per session scan A 437e329f6be3

Subscribe to this mod's changes

selectedleafs-telegram is a skill published in the GitHub repository wemwi/skill-library (1 stars, last pushed yesterday), with no licence file. It adds 189 tokens to every session and 7,548 once invoked, about $0.0008 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 2026-08-31.

Related

Other skills, from other repositories

offensive-crypto-attacks

Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and…

SnailSploit/Claude-Red · 261 tokens

offensive-parameter-pollution

HTTP parameter pollution (HPP) checklist: duplicate parameter injection, backend vs frontend parsing differences, WAF bypass via HPP, server-side vs client-side HPP, and practical exploitation patterns. Use when testing web applications for parameter handling flaws.

SnailSploit/Claude-Red · 0 tokens

offensive-z-wave

Z-Wave attack methodology — sniffing with Z-Force / EZ-Wave / RTL-SDR + ZniffMobile, S0 (legacy) network-key derivation flaw and key reuse, S2 (modern) ECDH commissioning analysis, replay/injection on unauthenticated nodes, default-key brute-force on test deployments, and home-automation hub pivots. Use when targeting…

SnailSploit/Claude-Red · 113 tokens

feature-prioritisation

Aplica marcos de priorización (RICE, MoSCoW, Kano, ICE, Opportunity Scoring) para clasificar características e items del backlog. Úsalo cuando se te pida priorizar características, clasificar un backlog, decidir qué construir a continuación, o evaluar compensaciones entre ideas competidoras. Produce una lista de…

mohitagw15856/pm-claude-skills · 103 tokens

outcome-tracker

Record the testable predictions inside a decision, then score them against reality later — so frameworks earn trust from outcomes, not vibes. Use when committing to a prioritisation, forecast, or plan (to log what it predicts), when asked to review what actually happened, or to compute how well-calibrated past RICE…

mohitagw15856/pm-claude-skills · 100 tokens

job-application

Tailors a CV and cover letter to a specific job description. Use when asked to write a cover letter, tailor a CV or resume, optimise for ATS, match a job description, or prepare a job application. Produces an ATS-optimised tailored CV summary and a personalised cover letter aligned to the role's requirements.

mohitagw15856/pm-claude-skills · 69 tokens