BD ergocare-coach
Your personal desk health coach with automated break reminders. Generates platform-specific scripts (bash/PowerShell) for 20-20-20 eye care, lower back exercises, and RSI prevention. Comprehensive exercise routines, ergonomic guidance, and customizable notification systems for computer professionals.
Your personal desk health coach with automated break reminders.
As a process D 43/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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.
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
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
medium Dangerous commands
cmd-persistenceREADME.md:216Persistence mechanism (cron / launchd / scheduled task / autorun registry) (detector / deny-list definition)- Crontab: `@reboot /path/to/ergocare.sh`
detector -
medium Dangerous commands
cmd-persistenceSKILL.md:561Persistence mechanism (cron / launchd / scheduled task / autorun registry) (detector / deny-list definition)- Add to startup (`crontab @reboot`)
detector
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5036 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 43/100
- 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
- 30Running it twice. 8 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Execution cost. Instruction body is 5036 tokens
- 85Steps. 149 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- low 16 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
- -245 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 301: enough signal without eating the budget
- +4Structure: 70 headings
- +3Step-by-step instructions: 149 items
- +4Has examples (35 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.