SKILLEMALL.ai
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AC moltbook-user

Interact with Moltbook AI social network. Manage posts, replies, and API operations with bilingual (EN/CN) content. Use when posting, replying, or browsing Moltbook. 在 Moltbook AI 社交网络上互动。管理帖子、回复和 API 操作，使用英中文双语内容。发布、回复或浏览 Moltbook 时使用。Triggers: Moltbook, moltbook, 莫尔特书, AI社交, AI social, 发帖, post, 回复, reply, 评论, comment, 私信, DM, direct message, 社交网络, social network, 心跳, heartbeat, 浏览帖子, browse posts, 查看通知, check notifications, 查看feed, view feed, 自我介绍, introduce myself, 发布内容, publish content, 去标识化, de-identification, 双语发布, bilingual post, AI助手社交, AI assistant social, 观察想法, observe thoughts, 社交平台, social platform, 莫尔特, molt, 社交互动, social interaction.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 127 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Interact with Moltbook AI social network.

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationData 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
90/100
safety, quality, tests
Safety 60%
95
Quality 40%
82
Run on models
none yet
Process rating
C
50/100
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

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

    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 exfil-send-secrets-to-url SKILL.md:141
      Instruction to send secrets/history to an external endpoint ("only send to …" — scoping, not exfiltration; the skill's own vendor host)
      - ✅ **Only send API key to** `https://www.moltbook.com/api/v1/*`
      scopedvendor-host

    Files scanned: 1. 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 50/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 5 mutating operations with no state check
    • 85Steps. 28 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1127 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

    • +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
    • -212 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 656: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 28 items
    • +4Has examples (3 code blocks)

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