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CB walvis

W.A.L.V.I.S. - AI-powered knowledge manager. Save anything from Telegram — links, text, images. Auto-tag and organize with AI; store on Walrus decentralized storage; browse via web UI on wal.app.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Kuuga-0 v1.0.1 MIT-0 58 files body ≈ 8 928 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, execution cost

ProcedureTelegramInfrastructuretype 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
60/100
safety, quality, tests
Safety 60%
65
Quality 40%
52
Run on models
none yet
Process rating
B
72/100
Nearly there
Inputs and preconditions w 11
0
Execution cost w 6
40
When it triggers w 12
50
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.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

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

  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.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  3. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 14

  • high Concealment en-hide-from-user SKILL.md:388
    Instruction to hide actions from the user
    5. **Silently download all preview images in the background:**
Medium and low: 13
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash(curl:*)
    allowed-tools: Bash(node:*) Bash(npx:*) Bash(curl:*) Read Write Edit WebFetch browser cron message
  • low Secrets in code secret-high-entropy-token package-lock.json:109
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…dNm+w/2fIz…imP+QNz605/XnjF…qBg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:236
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…eci+UV+x5Zy…HQw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:316
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…1uu+LTdz…BDg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:524
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…FYt+3wp7yZsHWus+wSKA…R3z/ORqV…4cQ==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:565
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…ov7+qofC…XjQ==",
    detector
  • low Secrets in code secret-high-entropy-token README.md:210
    High-entropy token-like string (may be an id, hash or a credential)
    6CaR…wis
  • low Secrets in code secret-high-entropy-token web/package-lock.json:251
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…3bJ+V0If…IXN+CL65…a4w==",
    detector
  • low Secrets in code secret-high-entropy-token web/package-lock.json:354
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…SzS+cfgl…B0A==",
    detector
  • low Secrets in code secret-high-entropy-token web/package-lock.json:367
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…Om3+5ZRS…Lw6+EGyk…kl3+UP9+sdz7…Y3g==",
    detector
  • low Secrets in code secret-high-entropy-token web/package-lock.json:373
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…7pY+zoMV…h0x/Ptw8…8dg==",
    detector
  • low Secrets in code secret-high-entropy-token web/package-lock.json:389
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…b00+Gxjx…zRc/oZwU…hzA==",
    detector
  • low Secrets in code secret-high-entropy-token web/src/routes/index.tsx:27
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    blobId: '6CaR…wis',
    quoted

Files scanned: 45. 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")
  • warning body-long SKILL.md body ≈ 8928 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "metadata.openclaw"

Process rating: all ten parameters 72/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 40Execution cost. Instruction body is 8928 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 258 steps, 1 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Failures and branches. 33 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (20 tags): a typed call is more reliable

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)
  • -5TODO / placeholder text left in the skill
  • -2localhost URLs: will not work for another user
  • -230 emoji in the instructions: noise for the model
  • -32 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 195: enough signal without eating the budget
  • +4Structure: 70 headings
  • +3Step-by-step instructions: 258 items
  • +3Output format is stated explicitly
  • +4Has examples (57 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 52.

External checks

ClawHub: suspicious
WALVIS is a real knowledge-manager skill, but it makes broad persistent OpenClaw changes and can use local wallet keys for blockchain access-control actions.
LLM: suspicious (high) · VirusTotal: · 29 May 2026