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BC tg-stickers

Collect and send Telegram stickers smartly. Auto-import packs, tag by emotion, select contextually, and respect frequency limits (2-5 messages).

ClawHub Agent Skills author: Ben Zhang v0.2.0 7 files · 4 scripts body ≈ 1 108 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureTelegramAI and agentsSoftware developmenttype 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
B
86/100
safety, quality, tests
Safety 60%
96
Quality 40%
70
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 4

✓ No critical or high findings

Medium and low: 4
  • low Secrets in code secret-high-entropy-token import-sticker-pack.sh:19
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    echo "  $0 p_8R…Bot"
    quoted
  • low Exfiltration exfil-webhook-url import-sticker-pack.sh:31
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    RESPONSE=$(curl -s "https://api.telegram.org/bot$BOT_TOKEN/getStickerSet?name=…")
    placeholder
  • low Exfiltration net-credential-use import-sticker-pack.sh:31
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    RESPONSE=$(curl -s "https://api.telegram.org/bot$BOT_TOKEN/getStickerSet?name=…")
    vendor-host
  • low Secrets in code secret-high-entropy-token README.md:17
    High-entropy token-like string (may be an id, hash or a credential)
    ./import-sticker-pack.sh pa_Y…Bot

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 21 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1108 tokens

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
  • -224 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 144: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (8 code blocks)

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

External checks

ClawHub: suspicious
Prompt-injection indicators were detected in the submitted artifacts (unicode-control-chars); human review is required before treating this skill as clean.
LLM: suspicious (high) · VirusTotal: · 29 May 2026