SKILLEMALL.ai

BF health-mate

Executable OpenClaw health-report skill with Chinese, English, and Japanese report flows. It reads Markdown logs only from an explicitly configured MEMORY_DIR, writes reports and logs locally, can create a commented project-local config/.env template during setup, sanitizes local-LLM stdout before AI commentary is embedded into reports, separates monthly disease mode from balanced/fat-loss lifestyle mode, and only performs Tavily, webhook, or font-download network activity when the corresponding runtime options are configured.

ClawHub Agent Skills author: tankeito v1.5.4 MIT-0 21 files · 3 scripts body ≈ 2 554 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 42/100 · Will not run — References files that are not bundled: assets/NotoSansSC-VF.ttf, assets/NotoSansJP-VF.ttf, scripts/health_report_pro.py

IntegrationData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
92
Quality 40%
66
Run on models
none yet
Process rating
F
42/100
Will not run
References files that are not bundled: assets/NotoSansSC-VF.ttf, assets/NotoSansJP-VF.ttf, scripts/health_report_pro.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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.

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. The text references files that are not there: add them or drop the references.
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 · 4

✓ No critical or high findings

Medium and low: 4
  • medium Exfiltration net-redirectable-api-key scripts/daily_report_pro.py:2780
    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
  • low Exfiltration exfil-webhook-url scripts/daily_health_report_pro.sh:112
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    req = urllib.request.Request(f'https://api.telegram.org/bot{TG_BOT_TOKEN}/sendMessage', data=data, headers={'Content-Type': 'application/json'})
    placeholder
  • low Exfiltration exfil-webhook-url scripts/monthly_health_report_pro.sh:113
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    req = urllib.request.Request(f'https://api.telegram.org/bot{TG_BOT_TOKEN}/sendMessage', data=data, headers={'Content-Type': 'application/json'})
    placeholder
  • low Exfiltration exfil-webhook-url scripts/weekly_health_report_pro.sh:120
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    req = urllib.request.Request(f'https://api.telegram.org/bot{TG_BOT_TOKEN}/sendMessage', data=data, headers={'Content-Type': 'application/json'})
    placeholder

Files scanned: 21. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: assets/NotoSansSC-VF.ttf
  • warning missing-ref reference to a missing file: assets/NotoSansJP-VF.ttf
  • warning missing-ref reference to a missing file: scripts/health_report_pro.py
  • warning missing-ref reference to a missing file: scripts/pdf_generator.py
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "type"
  • note frontmatter-key unknown frontmatter key "install"
  • note frontmatter-key unknown frontmatter key "capabilities"
  • note frontmatter-key unknown frontmatter key "env"

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: assets/NotoSansSC-VF.ttf, assets/NotoSansJP-VF.ttf, scripts/health_report_pro.py
  • 0Tools and files. 4 referenced file(s) missing: assets/NotoSansSC-VF.ttf, assets/NotoSansJP-VF.ttf, scripts/health_report_pro.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 10 mutating operations with no state check
  • 85Steps. 112 steps, 1 vague phrases
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2554 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 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
  • -311 of 15 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 532: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 112 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This health-report skill mostly matches its stated purpose, but it needs Review because crafted report text can become local Python code in its shell runners and sensitive health data flows lack strong guardrails.
LLM: suspicious (high) · VirusTotal: · 29 May 2026