AC engagelab-apppush
Call EngageLab App Push REST APIs to send push notifications and in-app messages to Android, iOS, and HarmonyOS devices; manage tags and aliases; create scheduled tasks and push plans; batch push; recall messages; query statistics; and configure callbacks. Use this skill when the user wants to send push notifications via EngageLab, manage device tags/aliases, schedule pushes, use batch single push, group push, message recall, delete users, query push statistics, validate push requests, upload images for OPPO, use push-to-speech, or integrate with EngageLab App Push. Also trigger for "engagelab push", "app push api", "push notification", "registration_id", "tag alias", "scheduled push", "push plan", "batch push", "message recall", "push statistics", "push callback", or "MTPush".
As a process C 59/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice
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: 6. 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 59/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 132 mutating operations with no state check
- 40Consistency. Frontmatter name (engagelab-apppush) differs from the folder (engagelab-app-push)
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Steps. 54 steps
- 100Execution cost. Instruction body is 3198 tokens
- low 18 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
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +5Description quotes 12 example trigger phrases
- +3Description length 788: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 54 items
- +3Output format is stated explicitly
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 99.