SKILLEMALL.ai

BC agent-hush

Invisible privacy guardian for agent workspaces. Automatically intercepts outbound actions (git push, skill publish, file sharing) and checks for sensitive data leaks. Users don't need to know commands — the agent handles everything silently. Activate on: ANY outbound action (push, publish, share, sync, send files), or when user asks "检查隐私", "有没有敏感信息", "privacy check", "scan for secrets".

ClawHub Agent Skills author: Elliot Liu v1.2.1 MIT-0 8 files body ≈ 1 433 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureGitHubAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
89
Quality 40%
82
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Secrets in code 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 files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • medium Secrets in code secret-private-key README_EN.md:130
      Private key material (detector / deny-list definition; key header without key body)
      - Private key blocks (`-----BEGIN PRIVATE KEY----- …
      detectorheader only
    • medium Secrets in code secret-private-key README.md:128
      Private key material (key header without key body; quoted — discussed, not commanded)
      - 私钥文件块(`-----BEGIN PRIVATE KEY----- …
      header onlyquoted
    • low Secrets in code secret-high-entropy-token scripts/sanitize.py:116
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      r'''bedr…29t''',
      detector

    Files scanned: 8. 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 62/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 15 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, git) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 100Steps. 20 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1433 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 391: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    This skill appears to be a local privacy scanner, but its silent automatic workspace scans and optional file-changing features should be reviewed before installation.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026