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 moshthepitt/lionclaw --skill channel-telegramgit clone --depth 1 https://github.com/moshthepitt/lionclawWrote 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/moshthepitt/lionclaw/channel-telegram)<a href="https://agentmods.dev/skills/moshthepitt/lionclaw/channel-telegram"><img src="https://agentmods.dev/badge/skills/moshthepitt/lionclaw/channel-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.
<a href="https://agentmods.dev/skills/moshthepitt/lionclaw/channel-telegram"><img src="https://agentmods.dev/badge/skills/moshthepitt/lionclaw/channel-telegram.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00022 | $0.02181 |
| Opus 5 | $0.00011 | $0.01091 |
| Sonnet 5 | $0.00004 | $0.00436 |
| Haiku 4.5 | $0.00002 | $0.00218 |
Grade A, and why
channel-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 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.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Telegram Channel Worker
Use this skill when the user wants Telegram as a LionClaw channel.
Manual QA and Telegram-specific acceptance notes live in README.md in this
skill directory.
What you run:
- start LionClaw for background work,
- run the Telegram worker,
- let it bridge Telegram traffic into LionClaw.
Under the hood, the worker:
- receives Telegram updates through long polling by default, or through an optional webhook receiver with Telegram secret-token verification,
- maps Telegram ids into stable refs such as
telegram:user:<id>,telegram:chat:<id>,telegram:topic:<id>, andtelegram:message:<id>, - posts normalized inbound facts to
/v0/channels/inboundand treats the response as admission state, not completed work, - claims
lc_...pairing tokens through the kernel pairing API without starting an agent turn for the claim message, - downloads and stages Telegram files only after the kernel returns
waiting_for_attachments, - long-polls
/v0/channels/stream/pullfor progress events, - starts Telegram typing from kernel queue/runtime status events,
- renders long-running turns as one provisional Telegram message and edits it on throttled progress state changes,
- renders inline buttons for safe active-turn controls such as status and stop,
- intercepts Telegram-local commands such as
/statusand/stopwithout stealing runtime slash commands such as/compact, - leases provider deliveries from
/v0/channels/outbox/pull, - sends Telegram messages from outbox leases and reports provider outcomes to
/v0/channels/outbox/report, - submits worker health checks through
/v0/channels/health/report, - advances its progress cursor through
/v0/channels/stream/ack.
Prerequisites
- a configured LionClaw project instance
- Telegram bot token with DM access
python3anduvfor source/development worker runs
Setup
Use the product path first:
printf 'TELEGRAM_BOT_TOKEN=...\n' > telegram.env
lionclaw connect telegram --env-file ./telegram.env
lionclaw doctor
What ships with it
13 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.
- lionclaw_channel_telegram/__init__.py 44 B runs code
- lionclaw_channel_telegram/__main__.py 89 B runs code
- lionclaw_channel_telegram/api.py 17 KB runs code
- lionclaw_channel_telegram/config.py 6.9 KB runs code
- lionclaw_channel_telegram/telegram.py 60 KB runs code
- lionclaw_channel_telegram/webhook.py 4.9 KB runs code
- lionclaw_channel_telegram/worker.py 146 KB runs code
- lionclaw.toml 116 B
- pyproject.toml 535 B
- README.md 5.4 KB
- scripts/worker 986 B
- tests/test_worker.py 468 KB runs code
- uv.lock 162 KB
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.
- 10d ago First seen · 182 lines · 22 tokens per session scan A 6b57fff6efe7
channel-telegram is a skill published in the GitHub repository moshthepitt/lionclaw (16 stars, last pushed 9d ago), licensed MIT. It adds 22 tokens to every session and 2,181 once invoked, about $0.0001 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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