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CD TeamClaw

A high-performance Agent subsystem designed for complex multi-agent orchestration (OASIS),automated computer use tasks, and real-time visual monitoring via a dedicated Web UI.

ClawHub Agent Skills author: BorisGuo v0.1.0 58 files · 8 scripts body ≈ 3 852 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI 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
C
66/100
safety, quality, tests
Safety 60%
63
Quality 40%
70
Run on models
none yet
Process rating
D
41/100
Unfinished process
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

The same skill appears in 1 more place: ClawHub

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.

Dangerous commands 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 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.

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 · 13

    ✓ No critical or high findings

    Medium and low: 13
    • medium Exfiltration net-redirectable-api-key chatbot/QQbot.py:22
      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
    • medium Exfiltration net-redirectable-api-key chatbot/telegrambot.py:14
      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
    • medium Exfiltration net-redirectable-api-key oasis/server.py:703
      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
    • medium Dangerous commands cmd-pipe-to-shell-known-host scripts/setup_env.sh:17
      Pipe-to-shell installer from a well-known host (still executes remote code)
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • medium Exfiltration net-redirectable-api-key src/llm_factory.py:84
      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
    • medium Exfiltration net-redirectable-api-key src/mainagent.py:553
      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
    • low Secrets in code secret-password-literal selfskill/scripts/adduser.py:28
      Hard-coded password / key literal (may be an example)
      username, password = sys.argv[1], sys.argv[2]
    • low Dangerous commands cmd-background-process selfskill/scripts/run.sh:46
      Starts a background / autostarted process
      nohup python scripts/launcher.py > "$PROJECT_ROOT/logs/launcher.log" 2>&1 &
    • low Exfiltration read-dotenv selfskill/scripts/run.sh:53
      Reads a .env file
      source config/.env 2>/dev/null || true
    • low Exfiltration read-dotenv selfskill/scripts/run.sh:100
      Reads a .env file
      source config/.env 2>/dev/null || true
    • low Exfiltration exfil-webhook-url src/mcp_bark.py:114
      Webhook / callback URL commonly used for exfiltration (verify the destination) (security demo / example; quoted — discussed, not commanded)
      :param public_url: The public URL (e.g. "https://xxx.trycloudflare.com")
      demoquoted
    • low Dangerous commands cmd-privilege src/mcp_commander.py:94
      Privilege escalation / world-writable permissions (string literal in code, not executed)
      "> /dev/sd", "chmod 777 /", "chown root", "/etc/passwd", "/etc/shadow",
      code literal
    • low Exfiltration exfil-webhook-url src/mcp_telegram.py:24
      Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
      TELEGRAM_API = f"https://api.telegram.org/bot{TELEGRAM_BOT_TOKEN}"
      placeholder

    Files scanned: 56. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 41/100

    • 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. 3 mutating operations with no state check
    • 40Consistency. Frontmatter name (TeamClaw) differs from the folder (teamclaw-2)
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 100Steps. 49 steps
    • 100Execution cost. Instruction body is 3852 tokens
    • 100Progress reporting. Reports progress
    • 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

    • +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
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • -2localhost URLs: will not work for another user
    • -37 of 7 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 175: enough signal without eating the budget
    • +4Structure: 37 headings
    • +3Step-by-step instructions: 49 items
    • +4Has examples (24 code blocks)

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

    External checks

    ClawHub: suspicious
    TeamClaw appears to be a real multi-agent service, but it exposes powerful agent, credential, tunnel, and code-execution features with weak controls that users should review before installing.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026