SKILLEMALL.ai
GitHub ↗ RU Sign in

AC vibo-selfdeed

Use when the owner hands the agent a multi-step task: grill the intent first (G1-G5 plan card, owner gate), then run it as an autonomous mission — restore context from ViBo memory, find and fix problems safely, iterate via paths A/B/C, save lessons. Optional Telegram notify/ask/report (OFF by default, runtime-warned; sends mission data only when the owner sets TELEGRAM_MISSION_TOKEN/CHAT). Built-in DEMO memory (100 facts) works without the ViBo CLI. Use ONLY with the user's explicit consent: missions save progress and lessons to local memory — tell the user what will be stored and how to delete it before starting.

ClawHub Agent Skills author: ViBo v1.0.13 MIT-0 12 files · 1 script body ≈ 2 868 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Use when the owner hands the agent a multi-step task: grill the intent first (G1-G5 plan card, owner gate), then run it as an autonomous mission — restore…

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

ProcedureTelegramData and analyticsAI and agentsLearningtype 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%
99
Quality 40%
82
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration exfil-webhook-url telegram_mission.py:35
      Webhook / callback URL commonly used for exfiltration (verify the destination) (the skill's own vendor host; quoted — discussed, not commanded)
      API = "https://api.telegram.org/bot"
      vendor-hostquoted

    Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "permissions"

    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. 10 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, git, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 75 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2868 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (13 tags): a typed call is more reliable

    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
    • -223 emoji in the instructions: noise for the model
    • +2Single-language instructions
    • +3Description length 621: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 75 items
    • +4Has examples (2 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: clean
    This skill is a disclosed local mission-runner with memory, backups, opt-in auto mode, and optional Telegram notifications, with risks users should understand but no artifact-backed malicious behavior.
    LLM: benign (high) · VirusTotal: · 31 Aug 2026