SKILLEMALL.ai

DD email-checker-for-mac

Automated email assistant for Apple Mail. Runs on a schedule, scores priority, drafts AI replies, and emails you a report. Manage your inbox from Telegram or WhatsApp — never open the bot inbox again.

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: entzclaw v1.1.1 MIT-0 11 files · 3 scripts body ≈ 384 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches

GeneratorTelegramWhatsAppData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
D
57/100
safety, quality, tests
Safety 60%
47
Quality 40%
71
Run on models
none yet
Process rating
D
46/100
Unfinished process
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

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.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

Exfiltration 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 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. 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.
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 · 7

  • high Dangerous commands cmd-persistence setup.sh:349
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    ( crontab -l 2>/dev/null | grep -v checker_wrapper || true
  • high Dangerous commands cmd-persistence setup.sh:353
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    ) | crontab -
Medium and low: 5
  • medium Exfiltration net-redirectable-api-key setup.sh:142
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • medium Dangerous commands cmd-persistence setup.sh:351
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    echo "@reboot $WRAPPER"
    code literal
  • medium Dangerous commands cmd-persistence setup.sh:358
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    echo "    @reboot $WRAPPER"
    code literal
  • low Dangerous commands cmd-cron-mention README.md:140
    Mentions editing / listing crontab (quoted — discussed, not commanded)
    Default: every hour. Change by editing crontab (`crontab -e`):
    quoted
  • low Dangerous commands cmd-cron-mention setup.sh:349
    Mentions editing / listing crontab
    ( crontab -l 2>/dev/null | grep -v checker_wrapper || true

Files scanned: 11. 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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 46/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 40Consistency. Frontmatter name (email-checker-for-mac) differs from the folder (email-checker-by-entzai)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 9 steps
  • 100Execution cost. Instruction body is 384 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 200: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This email assistant matches its stated purpose, but it needs careful review because it can control Mail, send reports and replies, run on a schedule, send email content to LLM providers, and contains unsafe or incomplete AppleScript handling.
LLM: suspicious (high) · VirusTotal: · 29 May 2026