SKILLEMALL.ai

CC zoomeye-ai-search

ZoomEye AI cyberspace search engine CLI. Use when searching global network assets, querying ZoomEye data, building ZoomEye AI dork queries, or conducting security research (asset discovery, vulnerability impact assessment, Bug Bounty, CVE correlation). CLI command: zoomeyeai, package: zoomeyeai, domain: zoomeye.ai.

ClawHub Agent Skills author: JJBondOne v1.0.0 MIT-0 2 files body ≈ 4 320 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

ZoomEye AI cyberspace search engine CLI.

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

IntegrationGitLabMySQLSecuritySales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
C
85/100
safety, quality, tests
Safety 60%
93
Quality 40%
74
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

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 · 7

    ✓ No critical or high findings

    Medium and low: 7
    • low Risky intent intent-offensive-security skill-card.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ZoomEye AI cyberspace search engine CLI for searching global network assets, querying ZoomEye data, building ZoomEye AI dork queries, and conducting security research for asset discovery, vulnerabilit
    • low Risky intent intent-offensive-security skill-card.md:17
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Security researchers, developers, and engineers use this skill to form ZoomEye AI search queries, check CLI readiness, and run cyberspace asset searches for CVE impact analysis, Bug Bounty discovery, 
    • low Risky intent intent-offensive-security SKILL.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      description: ZoomEye AI cyberspace search engine CLI. Use when searching global network assets, querying ZoomEye data, building ZoomEye AI dork queries, or conducting security research (asset discover
    • low Risky intent intent-offensive-security SKILL.md:19
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Bug Bounty asset discovery and filtering
    • low Risky intent intent-offensive-security SKILL.md:218
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | `is_bugbounty` | Bug Bounty program assets | `is_bugbounty=true` |
    • low Risky intent intent-offensive-security SKILL.md:219
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      | `bugbounty.source` | Bug Bounty data source | `bugbounty.source="hackerone"`, `"bugcrowd"`, `"intigriti"`, `"yeswehack"`, `"openbugbounty"`, `"all"` |
      detector
    • low Risky intent intent-offensive-security SKILL.md:266
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (documentation table row)
      | "Bug Bounty assets", "bounty program" | `is_bugbounty` | `is_bugbounty=true` |
      table

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: ZoomEye AI cyberspace search engine CLI. Use when searching global… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 61/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4320 tokens
    • 100Steps. 20 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 316: enough signal without eating the budget
    • +4Structure: 43 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (14 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

    External checks

    ClawHub: suspicious
    The skill is mostly a coherent ZoomEye search helper, but it tells users to share an API key in chat and have the agent place it on the command line.
    LLM: suspicious (high) · 16 Sept 2026