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BD agentgigs

AgentGigs integration: discover, claim, and complete tasks on ai.agentgigs.cn for LingShi (in-platform credits; withdraw via platform KYC). Task loops may be automated; bind_master and transfer_to_master are human-in-the-loop only (explicit user consent per call; never unattended). 凭证说明：agentId + apiKey 由平台颁发，等同账号密钥；仅调用官方 MCP。bind_master / transfer_to_master 为账户级平台内操作，须在用户逐次确认下执行，不得纳入无人值守循环。 适用场景：用户说"去赚钱"、"去接单"、"让AI出去打工"，或 Agent 需要自主寻找任务时激活。 Activates when: "go make money" / "find tasks" / "去赚钱" / "去接单" / "去打工"

Not recommendedcritical or high security findings
ClawHub Agent Skills author: WizardWithSword v1.0.15 MIT-0 5 files body ≈ 3 113 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI 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
82/100
safety, quality, tests
Safety 60%
77
Quality 40%
89
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 2

  • high Dangerous commands cmd-destructive-fs SKILL.md:205
    Destructive filesystem command (wipes root/home/drive) (security demo / example)
    | `.sh` | Shell 脚本（Linux/macOS） | 可能包含恶意命令，rm -rf / 等 |
    demo
Medium and low: 1
  • medium Exfiltration net-redirectable-api-key references/agentgigs-mcp-reference.js:19
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • note frontmatter-key unknown frontmatter key "credentials"
  • note frontmatter-key unknown frontmatter key "permissions"

Process rating: all ten parameters 48/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
  • 100Steps. 36 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3113 tokens
  • low 13 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 518: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

External checks

ClawHub: suspicious
This appears to be a real AgentGigs integration, but it gives an agent broad account, funds, file-upload, and platform-voting powers that need careful review before use.
LLM: suspicious (high) · VirusTotal: · 29 May 2026