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.
npx skills add serejaris/telegram-skills --skill tg-markdown-to-richgit clone --depth 1 https://github.com/serejaris/telegram-skillsWrote 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.
[](https://agentmods.dev/skills/serejaris/telegram-skills/tg-markdown-to-rich)<a href="https://agentmods.dev/skills/serejaris/telegram-skills/tg-markdown-to-rich"><img src="https://agentmods.dev/badge/skills/serejaris/telegram-skills/tg-markdown-to-rich/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.
<a href="https://agentmods.dev/skills/serejaris/telegram-skills/tg-markdown-to-rich"><img src="https://agentmods.dev/badge/skills/serejaris/telegram-skills/tg-markdown-to-rich.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.01691 |
| Opus 5 | $0.00049 | $0.00846 |
| Sonnet 5 | $0.00020 | $0.00338 |
| Haiku 4.5 | $0.00010 | $0.00169 |
Grade A, and why
tg-markdown-to-rich 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.
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.
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
tg-markdown-to-rich
The converter uses Python 3 standard library only. Direct sending requires network access to
api.telegram.org and TELEGRAM_BOT_TOKEN.
Converts a Markdown file (or stdin) into a Telegram InputRichMessage JSON
object. The output uses the markdown field of InputRichMessage and is ready
to pass directly to sendRichMessage.
See also: ../tg-rich-messages/SKILL.md for
composing rich messages programmatically.
Usage
# File input → stdout JSON
python3 scripts/md2rich.py document.md
# Pipe stdin
cat report.md | python3 scripts/md2rich.py
# Additional flags
python3 scripts/md2rich.py document.md --rtl
python3 scripts/md2rich.py document.md --skip-entity-detection
python3 scripts/md2rich.py document.md \
--media cover=photo=AgAC...file_id \
--media voice=voice_note=https://cdn.example.com/briefing.ogg
# Bindings with player metadata (duration, performer, title, has_spoiler)
python3 scripts/md2rich.py document.md --media-json bindings.json
# Upload local files: each attach://NAME needs a matching --attach NAME=PATH
python3 scripts/md2rich.py document.md \
--media-json bindings.json \
--attach cover_file=./cover.png \
--attach answer_file=./answer.mp3
# Send directly via Telegram Bot API (multipart when --attach is used)
TELEGRAM_BOT_TOKEN=<token> python3 scripts/md2rich.py document.md \
--send --chat-id <chat_id>
--media covers the common ID=TYPE=SOURCE case. Use --media-json when a binding needs
fields that syntax cannot express — an audio track's duration, performer, and title,
or has_spoiler on a photo:
[
{
"id": "answer",
"media": {
"type": "audio",
"media": "attach://answer_file",
"duration": 4,
"performer": "Voice 2.0",
"title": "Answer: 323"
}
}
]
Exit codes
| Code | Meaning |
|---|---|
0 |
Converted, or sent and acknowledged |
1 |
Definite failure — limit exceeded, bad binding, or a 4xx from Telegram |
2 |
Unknown outcome — 429, 5xx, or a transport failure during --send |
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.
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.
- 12d ago First seen · 163 lines · 99 tokens per session scan A 99eafd8795ca
tg-markdown-to-rich is a skill published in the GitHub repository serejaris/telegram-skills (18 stars, last pushed 1mo ago), licensed MIT. It adds 99 tokens to every session and 1,691 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.
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