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CC clawpod

Read any website or search Google, even when sites block bots or are geo-restricted. Handles CAPTCHAs, JavaScript rendering, and anti-bot protection server-side via residential proxies. Returns HTML or structured JSON.

ClawHub Agent Skills author: codeninja23 v0.1.7 4 files body ≈ 1 812 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSoftware developmentInfrastructuretype 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
69/100
safety, quality, tests
Safety 60%
60
Quality 40%
83
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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.

Broad scope 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 8

    ✓ No critical or high findings

    Medium and low: 8
    • medium Exfiltration net-credential-use README.md:88
      Credential used in a network call (verify the destination is the intended service)
      curl --proto =https -s -H "Authorization: Bearer $MASSIVE_UNBLOCKER_TOKEN" \
    • medium Exfiltration net-credential-use README.md:92
      Credential used in a network call (verify the destination is the intended service)
      curl --proto =https -s -H "Authorization: Bearer $MASSIVE_UNBLOCKER_TOKEN" \
    • medium Exfiltration net-credential-use README.md:96
      Credential used in a network call (verify the destination is the intended service)
      curl --proto =https -s -H "Authorization: Bearer $MASSIVE_UNBLOCKER_TOKEN" \
    • medium Exfiltration net-credential-use README.md:100
      Credential used in a network call (verify the destination is the intended service)
      curl --proto =https -s -H "Authorization: Bearer $MASSIVE_UNBLOCKER_TOKEN" \
    • medium Exfiltration net-credential-use README.md:104
      Credential used in a network call (verify the destination is the intended service)
      curl --proto =https -s -H "Authorization: Bearer $MASSIVE_UNBLOCKER_TOKEN" \
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash(curl
      allowed-tools: Bash(curl --proto =https *)
    • medium Exfiltration net-credential-use SKILL.md:102
      Credential used in a network call (verify the destination is the intended service)
      curl --proto =https -s -H "Authorization: Bearer $MASSIVE_UNBLOCKER_TOKEN" \
    • medium Exfiltration net-credential-use SKILL.md:111
      Credential used in a network call (verify the destination is the intended service)
      curl --proto =https -s -H "Authorization: Bearer $MASSIVE_UNBLOCKER_TOKEN" \

    Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 60/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 85Steps. 26 steps, 1 vague phrases
    • 100Tools and files. Tools declared in frontmatter
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1812 tokens
    • 100Progress reporting. Reports progress
    • low 10 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 218: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (9 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: clean
    ClawPod is a disclosed third-party web-unblocking and Google search skill, with privacy and acceptable-use cautions users should understand before using it.
    LLM: benign (high) · VirusTotal: benign · 28 May 2026