AD rental-management
End-to-end property rental management SOP for Taiwan, covering the full landlord lifecycle: tenant sourcing, screening, lease signing, move-in/move-out inspection, maintenance handling, rent collection, dispute resolution, and lease renewal/termination. Supports both self-managed and 包租代管 (agency-managed) models. Use when: (1) Managing a rental property, (2) Training new property managers, (3) Setting up rental management systems, (4) Handling landlord-tenant disputes, (5) Planning property maintenance schedules.
End-to-end property rental management SOP for Taiwan, covering the full landlord lifecycle: tenant sourcing, screening, lease signing, move-in/move-out…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 8. 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 49/100
- 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
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (rental-management) differs from the folder (taiwan-rental-management)
- 100Tools and files. No external tools needed
- 100Steps. 20 steps
- 100Execution cost. Instruction body is 431 tokens
- 100Running it twice. No mutating operations
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
- -215 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 518: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.