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BC verifiable-data

Use the Cryptowerk Verifiable Data skill to implement an "Agent Flight Recorder" that creates an immutable, cryptographically verifiable audit trail for OpenClaw agent executions. Register execution hashes to maintain privacy, fetch blockchain seals, and verify proofs for AI workflows, decisions, and data artifacts. Use when the user requires deterministic, proof-carrying agent operations with local sidecar artifacts and no SDK dependency. This skill securely acquires service credentials and exclusively handles proof APIs without executing unrelated account actions or purchases.

ClawHub Agent Skills author: cryptowerk-main v1.0.0 MIT-0 12 files · 4 scripts body ≈ 376 tokens Open the sourceclawhub.ai↗ analyzed 8 d ago

Use the Cryptowerk Verifiable Data skill to implement an "Agent Flight Recorder" that creates an immutable, cryptographically verifiable audit trail for…

As a process C 52/100 · Has gaps — weak spots: result and completion, failures and branches, consistency

AnalyzerAI 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
B
94/100
safety, quality, tests
Safety 60%
99
Quality 40%
86
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-high-entropy-token scripts/cwcommon.py:119
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      respJson=apiRequest("issueapikey","dXdl…2oK Y25G…aAo=",{"requesterId": requesterId})
      quoted

    Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 52/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (verifiable-data) differs from the folder (agent-flight-recorder)
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 26 steps
    • 100Execution cost. Instruction body is 376 tokens

    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
    • -31 of 4 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 585: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    This proof-audit skill mostly matches its stated purpose, but it uses bundled/plaintext Cryptowerk credentials and sends file hashes to a remote service without an explicit confirmation step.
    LLM: suspicious (high) · VirusTotal: · 15 Jun 2026