Agricultural Output Forecasting

AdvisoryAudited by Static analysis on Apr 30, 2026.

Overview

No suspicious patterns detected.

Findings (0)

Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.

What this means

If run, the skill could keep operating after the intended forecasting task and consume resources or later change behavior if the self-evolution logic is expanded.

Why it was flagged

This script would continuously run a self-evolution module every 30 minutes. That long-running background behavior is not needed for crop-yield forecasting and is not bounded by the visible install metadata.

Skill content
while true; do
    echo "[$(date)] Evolving..." >> $LOG_FILE
    cd $SKILL_PATH && python3 scripts/self_evolve.py >> $LOG_FILE 2>&1
    sleep 1800
done
Recommendation

Do not run the auto-evolve daemon unless you explicitly want a background process; the publisher should remove it or make it opt-in, documented, scoped, and easy to stop.

What this means

Users may trust the skill’s privacy posture more than warranted and provide identifiers believing they are hashed when they are stored plainly in the local trial file.

Why it was flagged

The security documentation makes strong privacy claims, but the provided TrialManager code stores trial data directly under the supplied user_id key rather than hashing it, so the privacy description is materially inaccurate.

Skill content
Data Stored:
  - User ID (hashed)
...
- No sensitive data is stored in plain text
Recommendation

Treat the privacy claims cautiously. The publisher should either hash user IDs as documented or update the documentation to accurately describe stored data.

What this means

After the trial, forecasts may use a billing API key and deduct tokens from the associated SkillPay account.

Why it was flagged

The code reads SkillPay credentials from environment variables and sends the API key to the billing provider. This is expected for a paid SkillPay integration, but the registry metadata says no credentials or env vars are required.

Skill content
API_KEY = os.environ.get('SKILLPAY_API_KEY', '')
SKILL_ID = os.environ.get('SKILLPAY_SKILL_ID', '')
...
'X-API-Key': api_key
Recommendation

Only configure a SkillPay key you trust for this purpose, monitor charges, and note that the metadata under-declares the credential requirement.

What this means

Local usage records may remain after using the skill until the user deletes them.

Why it was flagged

The skill persists local trial state, including user identifiers and timestamps. This is purpose-aligned for free-trial tracking, but users should know it remains on disk.

Skill content
self.trial_dir = os.path.expanduser("~/.openclaw/skill_trial")
...
data[user_id] = {'used_calls': 0, 'first_use': datetime.now().isoformat()}
Recommendation

Use a non-sensitive user_id and delete ~/.openclaw/skill_trial/agricultural-output-forecasting.json if you want to remove the trial history.

What this means

Users may need to fetch or create unreviewed files to follow the documentation, which weakens provenance and reproducibility.

Why it was flagged

The getting-started instructions tell users to run demo.py, but the supplied manifest does not include demo.py. Other docs also reference absent setup files such as .env.example.

Skill content
python demo.py
Recommendation

Use only the reviewed files in the package, and ask the publisher to include or remove references to missing helper files.