SKILLEMALL.ai

CB sergei-mikhailov-tg-channel-reader

Let your agent read and monitor Telegram channels: fetch posts, captions, link previews, and comments from public or private channels and turn them into daily digests, summaries, and alerts. JSON or text output, unread tracking, via MTProto (Pyrogram or Telethon).

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Sergey Mikhaylov v0.11.1 MIT-0 11 files body ≈ 6 724 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 67/100 · Nearly there — weak spots: when it triggers, running it twice

ProcedureTelegramAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
C
62/100
safety, quality, tests
Safety 60%
62
Quality 40%
61
Run on models
none yet
Process rating
B
67/100
Nearly there
When it triggers w 12
20
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 5

  • high Concealment en-hide-from-user SKILL.md:492
    Instruction to hide actions from the user
    **Never invent causes.** Do not tell the user the session "expired" or "was
Medium and low: 4
  • medium Dangerous commands cmd-shell-rc README.md:54
    Writes to a shell startup file
    > echo 'export PATH="$HOME/.venv/tg-reader/bin:$PATH"' >> ~/.bashrc
  • medium Dangerous commands cmd-shell-rc README.md:203
    Writes to a shell startup file
    echo 'export PATH="$HOME/.venv/tg-reader/bin:$PATH"' >> ~/.bashrc
  • medium Dangerous commands cmd-shell-rc README.md:209
    Writes to a shell startup file
    echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.bashrc
  • medium Dangerous commands cmd-shell-rc SKILL.md:593
    Writes to a shell startup file
    echo 'export PATH="$HOME/.venv/tg-reader/bin:$PATH"' >> ~/.bashrc && source ~/.bashrc

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Let your agent read and monitor Telegram channels: fetch posts, ca… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning body-long SKILL.md body ≈ 6724 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 67/100

  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 26 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, read, web, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6724 tokens
  • 85Steps. 49 steps, 2 vague phrases
  • 100Failures and branches. 8 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 264: enough signal without eating the budget
  • +4Structure: 48 headings
  • +3Step-by-step instructions: 49 items
  • +3Output format is stated explicitly
  • +4Has examples (31 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: clean
This is a disclosed Telegram reader that needs a powerful local Telegram session, so the main risk is normal account/session exposure rather than hidden malicious behavior.
LLM: benign (high) · VirusTotal: · 3 Jul 2026