SKILLEMALL.ai

BF health-guardian

Proactive health monitoring for AI agents. Apple Health integration, pattern detection, anomaly alerts. Built for agents caring for humans with chronic conditions.

ClawHub Agent Skills author: CTsolutionsdev v1.0.0 6 files body ≈ 1 026 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process F 28/100 · Will not run — References files that are not bundled: scripts/summary.py

IntegrationInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
F
28/100
Will not run
References files that are not bundled: scripts/summary.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
This is a copy of a skill from another catalog; the rating counts the canonical one: health-guardian (ClawHub)

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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 · 0

✓ No critical or high findings

Files scanned: 6. 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")
  • warning missing-ref reference to a missing file: scripts/summary.py

Process rating: all ten parameters 28/100

Will not run. References files that are not bundled: scripts/summary.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/summary.py
  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (health-guardian) differs from the folder (egvert-health-guardian)
  • 100Steps. 29 steps
  • 100Execution cost. Instruction body is 1026 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 163: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (8 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
The skill’s health-monitoring purpose is coherent, but it needs review because it handles sensitive health data with misleading privacy language and persistent monitoring guidance.
LLM: suspicious (high) · VirusTotal: benign · 10 Sept 2026