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DC credara

(no description)

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: 0xGrainzy v1.0.0 MIT-0 33 files body ≈ 1 177 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
D
42/100
safety, quality, tests
Safety 60%
70
Quality 40%
0
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
When it triggers w 12
0
Inputs and preconditions w 11
0
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.

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.

Risky intent 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 purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.

For the author

Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.

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. Add a description to the frontmatter: without it the skill never triggers.
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 · 5

  • high Exfiltration intent-browser-credential-store privacy.html:165
    Accesses a browser credential / cookie store
    <p>Credara uses minimal cookies, limited to those strictly necessary for Platform operation:</p>
Medium and low: 4
  • medium Risky intent intent-wallet-secrets wallet-guide.html:125
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
    <strong>You cannot import this wallet into MetaMask</strong> (or any wallet that expects a private key / seed phrase). There is no private key to export &mdash; the wallet is a smart contract controll
  • medium Risky intent intent-wallet-secrets wallet-guide.html:143
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
    <li><strong>Credara will never ask for a seed phrase.</strong> Your bot wallet is a smart contract &mdash; it does not have a seed phrase. Anyone asking for one is attempting a scam.</li>
  • low Secrets in code secret-high-entropy-token spec/cap-1.md:50
    High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file; quoted — discussed, not commanded)
    - **Contract:** AgentIdentity (`0xc5…DB8`)
    fixturequoted
  • low Secrets in code secret-high-entropy-token wallet-guide.html:86
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    <li><strong>USDC</strong> &mdash; used for skill pack purchases, course enrollments, and assessment fees. Contract: <code>0x83…913</code></li>
    placeholder

Files scanned: 33. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger

Process rating: all ten parameters 50/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 30Running it twice. 2 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1177 tokens
  • 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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: suspicious
Credara appears purpose-built for agent registration and credentials, but it asks agents to handle accounts, tokens, wallets, assessments, and forum participation with materially unclear disclosure.
LLM: suspicious (high) · VirusTotal: · 29 May 2026