slop-writer 0.5.1

An MCP server and a skill that analyze a Telegram channel, wired into Claude Code or Codex by one command:

• Scrape posts (text, media, reactions, views, forwards, tags) and the comment threads under each.
• Track outward forwarders — outside channels that re-share your posts — and inward citations — channels you forwarded from.
• Build an append-only time-series of per-post metrics on every re-run, so you can watch engagement evolve.
• Pull subscriber growth/churn by acquisition source, and views by hour of day for the "best time to post" question.
• Audit who subscribed in the last ~48 hours and flag bot-farm accounts.
• Schedule, retime, and rewrite future posts, and ban the bots an audit flagged — the two write paths, each behind a permission prompt.

Backed by Telethon. Everything reaches the agent as MCP tools — thirteen of them, over a local SQLite DB (one file per channel) that a read-only SQL tool answers questions from.

This is my personal skill — I built it to manage my own channel, @fastnewsdev. It's shared here in case the patterns are useful to someone else running a Telegram channel.

Install

Two commands, run from the project where you want the analytics.

uv tool install slop-writer
slop-writer install     # wires Claude Code: MCP server, approval gate, the skill
slop-writer init        # Telegram credentials and the one-time login

install writes the slop-writer entry in .mcp.json, a permission block in .claude/settings.json (reads allowed, publishing and banning behind a prompt), and the skill into .claude/skills/slop-writer/; everything it writes is printed. The .mcp.json entry holds no machine-specific path, so it is safe to commit — a teammate clones, runs slop-writer init, and is done. Restart your MCP client afterwards: project configuration is read at session start only.

Codex, or both

--client picks which MCP client gets wired, and it is repeatable:

slop-writer install --client codex
slop-writer install --client claude --client codex

For Codex the equivalents land in one file, .codex/config.toml: the [mcp_servers.slop-writer] entry and, on first install only, an approval_mode = "prompt" table for each write tool (publishing and banning). Every install also writes an address block into AGENTS.md and a copy of the skill into .agents/skills/slop-writer/, whichever client you named — an agent that is neither can still find it.

Codex ignores a project's configuration until you trust the directory, and that trust lives in your own global config, which this command never writes. So a teammate who clones the repository has to answer Codex's trust prompt in the directory once; slop-writer init is the only other step. The entry itself carries no machine-specific path either.

Each client is wired independently: what a project holds for one says nothing about another, and "first install" is a property of a client. Cursor and the Copilot coding agent are still not written for — their launch directory is unverified — so install prints an entry for you to paste into their config yourself.

slop-writer uninstall with no flag removes every client's wiring; narrowed with --client it leaves the others alone. Neither form ever touches .tg-analytic/.

init asks for your Telegram API credentials (create them here), writes .tg-analytic/.env, and runs the login. Run it in your own terminal — Telethon prompts for the SMS code and 2FA password on stdin, so it cannot go through a tool call. It is additive and safe to re-run: it prompts only for what is missing and logs in only when there is no working session. The two commands are independent and work in either order.

The skill alone, without the server, still installs through the skills CLI:

npx skills@latest add Lancetnik/slop-writer

Both channels serve the same directory, so whichever runs last wins on disk.

All runtime state — .env, the Telethon session, per-channel *.db files, downloaded media — lives in a gitignored .tg-analytic/ at your project root, never inside the skill. init gitignores it for you: the session file is a live login to your Telegram account.

Usage

Inside your client, ask in plain language:

Analyze @some_channel — show me the most popular posts. Who's forwarding @some_channel? Which channels do they cite most often? Refresh metrics on the last 20 posts of @some_channel. How did the discussion group grow after Tuesday's post? Schedule this draft for Friday at 18:00.

The skill picks the tool, and the tool returns a Markdown summary the agent pastes back (top posts by views and reactions, top tags, outward forwarders and inward citations with their post ids) — usually the answer is right there without dropping into SQL.

Keeping the metric history usable

post_metrics is a time series, but only of the moments you actually scraped — it cannot be backfilled. A routine scrape of the latest N posts re-measures recent posts only, so an older post can sit forever on the single snapshot it got on its first day, and "how did this post do over time" then has nothing to answer from. Every so often, ask for a refresh over a spread of older ids too:

Refresh metrics on posts 340, 345, 350 and 355 of @yourchannel.

Views in particular keep climbing for months, so a post's snapshots are worth collecting long after it stops feeling current.

What the agent reads

• SKILL.md — which tool answers which question, and the four invariants that break an answer silently
• references/analysis.md — what the numbers mean and how they mislead, over references/schema.md
• references/publishing.md — the write discipline and queue semantics, plus references/markup.md

Contributing

skills/slop-writer/ is the shipped skill (packaged into the wheel and served to npx skills add from here — one directory, one version). src/slop_writer/ is the library and the MCP server it drives; tools/ holds dev-only scripts that are never shipped. CLAUDE.md has the working rules, CONTEXT.md the vocabulary, and docs/adr/ the decisions behind both.