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BC telebiz-mcp

Access Telegram data via MCP using the telebiz-tt browser client. Lists chats, reads messages, searches, manages folders, and sends messages through an authenticated Telegram session.

modbender/skill-library-mcp Agent Skills author: modbender MIT 13 files · 3 scripts body ≈ 2 507 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Access Telegram data via MCP using the telebiz-tt browser client.

As a process C 53/100 · Has gaps — weak spots: result and completion, consistency, running it twice

ProcedureTelegramAI and agentstype 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
84/100
safety, quality, tests
Safety 60%
94
Quality 40%
70
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
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 · 6

✓ No critical or high findings

Medium and low: 6
  • low Secrets in code secret-high-entropy-token package-lock.json:24
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-GZMB+a0mO…4cw+w1WV…UED+1X8a…sJi+8mgpw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:194
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…HK5+NE/tvnRLbIqUWa+0E9N4WNMjmp/kXXP…R8w==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:415
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…78O/B3Kkh+nKABUF++bvJv…56W+C8F9…X6m+IktJnIb1Jjg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:517
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…7sL+iGzu…aOw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:537
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…GLi+2W/6ao+6Y7gu/RCwR…Kng==",
    detector
  • low Dangerous commands cmd-background-process telebiz-service.sh:15
    Starts a background / autostarted process
    nohup telebiz-mcp >> "$LOG_FILE" 2>&1 &

Files scanned: 13. 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 53/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 24 mutating operations with no state check
  • 40Consistency. Frontmatter name (telebiz-mcp) differs from the folder (telebiz-mcp-skill)
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 46 steps, 1 vague phrases
  • 100Execution cost. Instruction body is 2507 tokens
  • 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

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
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 183: enough signal without eating the budget
  • +4Structure: 46 headings
  • +3Step-by-step instructions: 46 items
  • +4Has examples (19 code blocks)

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