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FC eo-collaboration

Everything Openclaw (EO) - Transform OpenClaw into a Steel Crayfish Legion with 141 experts, 9 commands, Skills dual system, and 15 core innovations

Blockedguard blocked the skill: signs of malicious behaviour
ClawHub Agent Skills author: 467718584 v2.2.0 MIT-0 80 files body ≈ 1 732 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorGitHubWriting and documentstype 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
F
32/100
safety, quality, tests
Safety 60%
10
Quality 40%
66
Run on models
none yet
Process rating
C
56/100
Has gaps
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
Guard blocked this skill: critical findings below. Do not install it until the author fixes them.
This is a copy of a skill from another catalog; the rating counts the canonical one: eo-collaboration (ClawHub)

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.

Exfiltration
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. Remove the critical guard findings (secrets, dangerous commands, hidden instructions): while they stand the skill is blocked and cannot grade above F.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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

  • critical Exfiltration exfil-send-secrets-to-url expert-library/marketing/marketing-carousel-growth-engine.md:143
    Instruction to send secrets/history to an external endpoint
    | `UPLOADPOST_TOKEN` | Upload-Post API token for publishing + analytics | https://upload-post.com → Dashboard → API Keys |
Medium and low: 12
  • low Risky intent intent-offensive-security expert-library/engineering/engineering-security-engineer.md:28
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    ### Vulnerability Assessment & Penetration Testing
  • low Risky intent intent-offensive-security expert-library/engineering/engineering-solidity-smart-contract-engineer.md:485
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - When access control gaps allow privilege escalation through role chaining
  • low Risky intent intent-offensive-security expert-library/engineering/engineering-threat-detection-engineer.md:32
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
    - Validate that detections actually fire by running atomic red team tests or purple team exercises
    detector
  • low Risky intent intent-offensive-security expert-library/engineering/engineering-threat-detection-engineer.md:58
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
    - Cover the full kill chain — detecting only initial access means you miss lateral movement, persistence, and exfiltration
    detector
  • low Risky intent intent-offensive-security expert-library/engineering/engineering-threat-detection-engineer.md:184
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | Privilege Escalation| 13        | 5       | 8    | 38%        |
  • low Risky intent intent-offensive-security expert-library/engineering/engineering-threat-detection-engineer.md:188
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | Lateral Movement    | 9         | 4       | 5    | 44%        |
  • low Risky intent intent-offensive-security expert-library/engineering/engineering-threat-detection-engineer.md:191
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | Command and Control | 16        | 5       | 11   | 31%        |
  • low Secrets in code secret-high-entropy-token expert-library/engineering/engineering-threat-detection-engineer.md:234
    High-entropy token-like string (may be an id, hash or a credential)
    run: pip install sigma-cli pySigma-backend-splunk pySi…der
  • low Secrets in code secret-high-entropy-token expert-library/engineering/engineering-threat-detection-engineer.md:273
    High-entropy token-like string (may be an id, hash or a credential)
    pySi…der \
  • low Risky intent intent-offensive-security expert-library/EXPERT_ROLES.md:65
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    Tasks: Security audit, vulnerability assessment, penetration testing
  • low Secrets in code secret-high-entropy-token expert-library/marketing/marketing-livestream-commerce-coach.md:127
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Campaign naming convention: date_audience_creative-type_bid, e.g., "0312…_35"
    quoted
  • low Secrets in code secret-high-entropy-token expert-library/marketing/marketing-short-video-editing-coach.md:262
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - File naming convention: date_project_shot-number_description, e.g., "2026…eup"
    quoted

Files scanned: 80. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 56/100

  • 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. 5 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 6 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1732 tokens
  • 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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -221 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 148: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 6 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This is a broad agent-collaboration plugin whose artifacts include under-scoped persistence, public posting/payment/deploy authority, and review tools that can give false confidence.
LLM: suspicious (high) · VirusTotal: · 29 May 2026