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Natural language search for local files (100G-1T). Supports xlsx, pptx, pdf, docx formats with location info. Triggered when user asks to search local/computer/folder content.

Not recommendedcritical or high security findings
LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 11 files · 2 scripts body ≈ 3 305 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Natural language search for local files (100G-1T).

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

IntegrationExcelPowerPointWordPostgreSQLAI 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
C
73/100
safety, quality, tests
Safety 60%
66
Quality 40%
83
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.

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.
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 · 9

  • high Dangerous commands cmd-persistence scripts/schedule_sync.sh:60
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null; echo "$cron_job") | crontab -
Medium and low: 8
  • medium Dangerous commands cmd-persistence scripts/schedule_sync.sh:56
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (detector / deny-list definition)
    crontab -l 2>/dev/null | grep -v "$SYNC_SCRIPT" | crontab -
    detector
  • medium Dangerous commands cmd-persistence scripts/schedule_sync.sh:72
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (detector / deny-list definition)
    crontab -l 2>/dev/null | grep -v "$SYNC_SCRIPT" | crontab -
    detector
  • low Dangerous commands cmd-cron-mention scripts/schedule_sync.sh:53
    Mentions editing / listing crontab
    if crontab -l 2>/dev/null | grep -q "$SYNC_SCRIPT"; then
  • low Dangerous commands cmd-cron-mention scripts/schedule_sync.sh:56
    Mentions editing / listing crontab
    crontab -l 2>/dev/null | grep -v "$SYNC_SCRIPT" | crontab -
  • low Dangerous commands cmd-cron-mention scripts/schedule_sync.sh:60
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null; echo "$cron_job") | crontab -
  • low Dangerous commands cmd-cron-mention scripts/schedule_sync.sh:71
    Mentions editing / listing crontab
    if crontab -l 2>/dev/null | grep -q "$SYNC_SCRIPT"; then
  • low Dangerous commands cmd-cron-mention scripts/schedule_sync.sh:72
    Mentions editing / listing crontab
    crontab -l 2>/dev/null | grep -v "$SYNC_SCRIPT" | crontab -
  • low Dangerous commands cmd-background-process scripts/start_server.sh:35
    Starts a background / autostarted process
    nohup khoj --anonymous-mode > /tmp/khoj.log 2>&1 &

Files scanned: 11. 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
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 38 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3305 tokens
  • 100Running it twice. No mutating operations
  • low 21 top-level sections: this looks like several domains in one skill

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
  • -2localhost URLs: will not work for another user
  • -214 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 175: enough signal without eating the budget
  • +4Structure: 67 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (29 code blocks)
  • +3All 5 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.