SKILLEMALL.ai
GitHub ↗ RU Sign in

FC workspace

(no description)

Not recommendedcritical or high security findings · low grade F
ClawHub Agent Skills author: AliGhotbizadeh v1.0.0 MIT-0 80 files · 10 scripts body ≈ 772 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

IntegrationJiraSoftware developmentOperations and projectstype 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
F
26/100
safety, quality, tests
Safety 60%
43
Quality 40%
0
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
When it triggers w 12
0
Running it twice w 4
30
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.

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. 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 · 11

  • high Dangerous commands cmd-persistence install_autostart.sh:34
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load "$PLIST_DEST"
  • high Dangerous commands cmd-persistence install_permanent_service.sh:65
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load "$PLIST_DEST"
Medium and low: 9
  • medium Broad scope meta-agent-memory-dump HEARTBEAT.md
    Agent memory / workspace files bundled with the skill (4) — likely a workspace dump with personal data or tokens
    HEARTBEAT.md, IDENTITY.md, SOUL.md, USER.md
  • medium Dangerous commands cmd-persistence install_autostart.sh:41
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    echo "   launchctl load $PLIST_DEST"
    code literal
  • medium Dangerous commands cmd-install-from-url jira_venv/lib/python3.14/site-packages/pip/__main__.py:12
    Installs a package from an untrusted URL / archive (code comment)
    # This allows the usage python pip-*.whl/pip install pip-*.whl
    comment
  • low Risky intent intent-offensive-security chapter6_clean.txt:49
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    در لایه شبکه، NetworkPolicy به␀منظور microsegmentation پیاده␀سازی شده است. سیاست پیش␀فرض برای ترافیک ورودی به Pod ها حالت deny دارد و ارتباطات مجاز فقط به␀صورت صریح تعریف می␀شوند. این رویکرد zero-trus
  • low Secrets in code secret-password-literal create_google_doc.py:201
    Hard-coded password / key literal (may be an example)
    password = "Q4Sswh3zG!tmv6T#"
  • low Dangerous commands cmd-background-process FINAL_SUMMARY.md:111
    Starts a background / autostarted process
    nohup ./start_prompts.sh start &
  • low Secrets in code secret-password-literal format_google_doc_selenium.py:157
    Hard-coded password / key literal (may be an example)
    password = "sYOY…86z"
  • low Secrets in code secret-high-entropy-token format_google_doc.py:15
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    DOCUMENT_ID = "10aU…c4s"
    quoted
  • low Risky intent intent-offensive-security google_docs_content.txt:276
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    در لایه شبکه، NetworkPolicy به␀منظور microsegmentation پیاده␀سازی شده است. سیاست پیش␀فرض برای ترافیک ورودی به Pod ها حالت deny دارد و ارتباطات مجاز فقط به␀صورت صریح تعریف می␀شوند. این رویکرد zero-trus

Files scanned: 80. 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 56/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 28 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 772 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

  • +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
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (11 code blocks)

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

External checks

ClawHub: suspicious
The Jira logging skill has a coherent core, but it bundles real credentials, unrelated Google/Word automation, and under-scoped background service installers.
LLM: suspicious (high) · VirusTotal: · 29 May 2026