SKILLEMALL.ai

BF Telegram News Digest (Lite)

Monitors public Telegram channels via web scraping (t.me/s/*), extracts new messages, generates AI-powered summaries, and delivers structured digests to your configured OpenClaw notification channel. Zero authentication required — just provide channel names.

ClawHub Hermes author: Garos v1.0.0 MIT-0 10 files body ≈ 3 620 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 33/100 · Will not run — References files that are not bundled: LICENSE

GeneratorTelegramInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
77/100
safety, quality, tests
Safety 60%
95
Quality 40%
51
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: LICENSE
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration 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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
  3. The text references files that are not there: add them or drop the references.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Exfiltration net-credential-use SKILL.md:380
    Credential used in a network call (verify the destination is the intended service)
    curl -H "Authorization: Bearer $OPENCLAW_GATEWAY_TOKEN" \

Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-long-hermes description is 259 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • warning missing-ref reference to a missing file: LICENSE
  • note frontmatter-key unknown frontmatter key "id"
  • note frontmatter-key unknown frontmatter key "minOpenClawVersion"
  • note frontmatter-key unknown frontmatter key "runtime"
  • note frontmatter-key unknown frontmatter key "permissions"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: LICENSE
  • 0Tools and files. 1 referenced file(s) missing: LICENSE
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 40Consistency. Frontmatter name (Telegram News Digest (Lite)) differs from the folder (tg-news-digest-lite)
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 25 steps
  • 100Execution cost. Instruction body is 3620 tokens
  • 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)
  • +3Output format is not stated: the model decides each time
  • -230 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 258: enough signal without eating the budget
  • +4Structure: 39 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (20 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 51.

External checks

ClawHub: clean
The skill coherently monitors public Telegram channels and summarizes them, but users should notice that channel text is sent to the configured LLM provider despite one confusing documentation line.
LLM: benign (medium) · VirusTotal: · 29 May 2026