BD movie-coupon
Fetch movie ticket coupons from platforms like Taopiaopiao and Maoyan. Returns coupon links and QR code images for users to redeem via WeChat.
The skill fetches movie ticket coupons from Taopiaopiao and Maoyan, returns links and QR codes for WeChat redemption. Narrowly scoped to Chinese platforms—worthless outside that ecosystem.
Grade B with quality_score 82 looks generous: process runs at 61%, no critical issues found, but the skill never ran on models. Three files, one script, linter passes. Security score maxed out, which makes sense—coupon scraping poses no threat.
Install if you're in China and need tickets. Otherwise skip it.
Fetch movie ticket coupons from platforms like Taopiaopiao and Maoyan.
As a process D 43/100 · Unfinished process — References files that are not bundled: assets/movie-sample1.png
The same skill appears in 2 more places: agentic-awesome-skills, agentic-awesome-skills
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- The text references files that are not there: add them or drop the references.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 142 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
missing-refreference to a missing file: assets/movie-sample1.png - note
frontmatter-keyunknown frontmatter key "risk" - note
frontmatter-keyunknown frontmatter key "source" - note
frontmatter-keyunknown frontmatter key "source_repo" - note
frontmatter-keyunknown frontmatter key "source_type" - note
frontmatter-keyunknown frontmatter key "date_added" - note
frontmatter-keyunknown frontmatter key "tools"
Process rating: all ten parameters 43/100
- 0Tools and files. 1 referenced file(s) missing: assets/movie-sample1.png
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70When it triggers. States when to use, but not when not to
- 85Steps. 20 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1268 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
- +1No license
- +2Single-language instructions
- +3Description length 142: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.