SKILLEMALL.ai
GitHub ↗ RU Sign in

AC tg-message-assistant

Generate topic briefings from Telegram channels. Use this skill when the user mentions "briefing", "newsletter", "digest", "message summary", "channel recap", "generate report", "send briefing", "scheduled push", or "channel roundup". Also applies when users want to compile messages from multiple Telegram channels into structured summaries and deliver them to others.

ClawHub Agent Skills author: TelyClaw v1.0.0 MIT-0 10 files body ≈ 469 tokens Open the sourceclawhub.ai↗ analyzed 30 h ago

Generate topic briefings from Telegram channels.

As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorTelegramGmailWriting and documentsSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    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 · 0

    ✓ No critical or high findings

    Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 56/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 5 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 11 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 469 tokens
    • 100Progress reporting. Reports progress

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 9 example trigger phrases
    • +3Description length 369: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 11 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: clean
    This skill is a Telegram briefing helper that clearly discloses its use of Telegram, Gmail, OAuth/browser sessions, and optional scheduling, with no evidence of hidden or destructive behavior.
    LLM: benign (high) · VirusTotal: · 10 Jun 2026