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 glebis/claude-skills --skill tg-respondergit clone --depth 1 https://github.com/glebis/claude-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/glebis/claude-skills/tg-responder)<a href="https://agentmods.dev/skills/glebis/claude-skills/tg-responder"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/tg-responder/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/glebis/claude-skills/tg-responder"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/tg-responder.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 | $0.00067 | $0.01005 |
| Opus 5 | $0.00034 | $0.00502 |
| Sonnet 5 | $0.00013 | $0.00201 |
| Haiku 4.5 | $0.00007 | $0.00101 |
Grade A, and why
tg-responder 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 8d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
tg-responder — Telegram Communications Assistant
Review pending response drafts and manage the Telegram response queue.
Commands
review — Approve pending drafts
Read the responder queue and present drafts for approval:
python3 ~/.claude/skills/tg-responder/scripts/schema.py # ensure DB exists
Then query the database:
-- Pending drafts needing approval
SELECT o.id, o.chat_id, o.draft_text, o.draft_reason, o.source,
i.sender_name, i.text as original_text, i.urgency, i.category,
datetime(i.received_at, 'unixepoch') as received
FROM outbox o
JOIN inbox i ON o.inbox_id = i.id
WHERE o.status = 'draft'
ORDER BY
CASE i.urgency WHEN 'urgent' THEN 0 WHEN 'normal' THEN 1 ELSE 2 END,
o.created_at ASC;
For each draft, present to the user:
- Original message — who sent it, when, what they said
- Draft response — the proposed reply
- Options: approve (send as-is), edit (modify then send), skip
To approve and send a draft:
- Update outbox:
UPDATE outbox SET status = 'approved', final_text = draft_text, approved_at = strftime('%s','now') WHERE id = ? - Send via telegram skill:
python3 ~/.claude/skills/telegram/scripts/telegram_fetch.py send --chat-id CHAT_ID --text "THE_TEXT" - Update outbox with sent status and message_id
To skip: UPDATE outbox SET status = 'skipped', updated_at = strftime('%s','now') WHERE id = ?
status — Queue statistics
-- Inbox stats
SELECT status, count(*) FROM inbox GROUP BY status;
-- Outbox stats
SELECT status, count(*) FROM outbox GROUP BY status;
-- Recent activity
SELECT sender_name, route, status, datetime(created_at, 'unixepoch')
FROM inbox ORDER BY created_at DESC LIMIT 10;
Report: pending count, drafts waiting, sent today, failed items.
follow-ups — Track unanswered outbound messages
Scan for people who haven't replied, send reminders with exponential backoff.
# Scan for new unanswered messages (needs Telethon session — stop daemon first)
python3 ~/.claude/skills/tg-responder/scripts/follow_ups.py scan
# Process due reminders (drafts to Telegram or outbox)
python3 ~/.claude/skills/tg-responder/scripts/follow_ups.py remind
# List active follow-ups
python3 ~/.claude/skills/tg-responder/scripts/follow_ups.py list
# Archive expired follow-ups
python3 ~/.claude/skills/tg-responder/scripts/follow_ups.py archive
# Run all (scan + check replies + remind + archive)
python3 ~/.claude/skills/tg-responder/scripts/follow_ups.py all
What ships with it
11 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.
- .gitignore 42 B
- prompts/classify.md 2.1 KB
- scripts/backfill.py 3.7 KB runs code
- scripts/classify.py 3.9 KB runs code
- scripts/follow_ups.py 17 KB runs code
- scripts/hook.py 2.8 KB runs code
- scripts/lookup_chat.py 1000 B runs code
- scripts/schema.py 7.0 KB runs code
- scripts/seed_templates.py 1014 B runs code
- scripts/tg_draft.py 1.5 KB runs code
- scripts/worker.py 16 KB runs code
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.
- 8d ago First seen · 115 lines · 67 tokens per session scan A abd6ec7ae39e
tg-responder is a skill published in the GitHub repository glebis/claude-skills (375 stars, last pushed 10d ago), licensed MIT. It adds 67 tokens to every session and 1,005 once invoked, about $0.0003 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 2026-09-03.
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