A Claude Code skill that analyzes a Telegram
channel:

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 broken down by acquisition source and views by hour of day for the "best time to post" question.
Schedule, retime, and rewrite future posts — the one write path.

Backed by Telethon. Everything reaches the agent as MCP tools — eleven 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

Renamed from tg-analytic-skill. The analytics are being repackaged as a
PyPI distribution driving an MCP server, and the new name leaves room for
media beyond Telegram. The setup below is the new one; links to the old
repository path still redirect.

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, permissions, the skill
slop-writer init        # Telegram credentials and the one-time login

install writes three things: the slop-writer entry in .mcp.json, a
permission block in .claude/settings.json (reads allowed, publishing behind a
prompt), and the skill into .claude/skills/slop-writer/. It deletes one — a
.claude/skills/tg-analytic-skill/ left by a pre-0.4 install, which would
otherwise load alongside the current skill and describe a surface that no
longer exists. Everything it writes or removes 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: .mcp.json is read at session start only.

Verified on Claude Code. For Cursor, Codex or the Copilot coding agent,
install prints the entry for you to paste into their config yourself.

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.

slop-writer uninstall removes exactly what install wrote. It never touches
.tg-analytic/.

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 session, per-channel *.db files, downloaded
media — lives in .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 Claude Code, 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 on the single snapshot it got on
its first day forever, and any "how did this post do over time" question then
has nothing to answer from. Every so often, ask for a refresh over a spread of
older post ids as well:

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.

The skill's own files, if you want to read 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

Repository layout

skills/
  slop-writer/        Shipped both ways: packaged into the wheel (so
                      `slop-writer install` can copy it out) and served to
                      `npx skills add` from here. One directory, one version.
    SKILL.md          Which tool answers which question, and the invariants.
    references/
      analysis.md     What the numbers mean, and how they mislead.
      publishing.md   Write discipline and scheduled-queue semantics.
      schema.md       DB schema reference for writing SQL.
      markup.md       Supported Markdown -> Telegram markup for post bodies.
src/
  slop_writer/        The library and the shipped server, published to PyPI. It
                      holds the domain logic; `server.py` and the dev CLIs in
                      `tools/` are argument parsing and output rendering over
                      it — two callers of one set of functions.
    db.py             DB schema (source of truth), paths, open helpers. Stdlib only.
    errors.py         SlopWriterError/UsageError — what the domain raises. Stdlib only.
    query.py          Read-only SQL guards and execution. Stdlib only.
    tg.py             Telethon session/credential plumbing.
    messages.py       Telethon Message -> plain fields (media, reactions, albums).
    scrape.py         The post pipeline: scrape_posts / refresh_posts.
    group.py          Discussion group: classification, thread linkage, scan_group.
    stats.py          Broadcast stats: subscribers, views by hour.
    scheduled.py      Reading the scheduled queue.
    publish.py        The write surface: schedule / reschedule / edit.
    render.py         Markdown renderers for the per-command summaries.
    markdown.py       Markdown -> Telethon MessageEntity (publish only).
    server.py         The MCP server and its read tools.
    install.py        `install`/`uninstall`: the agent wiring. No Telegram.
    init.py           `init`: credentials, gitignore, the TTY login. No MCP.
    cli.py            The `slop-writer` console script (argparse).
tools/               Dev-only, never shipped to users.
  check_schema_doc.py  Guard SCHEMA <-> references/schema.md drift. Pinned to
                       this checkout, not to the released package, so it guards
                       the working tree.
  tg_scrape.py         The old read CLI (scrape, fetch, group, subscribers,
  tg_publish.py        views, scheduled), write CLI and SQL CLI. Undocumented
  tg_query.py          and unsupported: the MCP tools are the surface now.
                       Kept because `login` needs a TTY and because they are
                       the only way to exercise Telethon without a client.

Runtime state (.env, the Telethon session, per-channel *.db files, media)
lives in a gitignored .tg-analytic/ directory at the root of whatever
project you run the skill from — nothing is written inside the skill itself.

Install

Usage

Keeping the metric history usable

Repository layout

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