BC trip-coupon
Call trip/travel coupon API to fetch travel coupons including DiDi ride-hailing gift packages and hotel coupon bundles. Returns coupon links and QR code images for users to redeem via WeChat.
This skill integrates a travel coupon API: fetches DiDi ride codes and hotel packages, returns redemption links and QR codes for WeChat. Three files, one script, no critical issues. Quality score 82, but process score 61 suggests limited automation in the workflow.
Security checks passed perfectly (100), no critical findings. Models weren't tested, sandbox wasn't run—actual behavior on live requests remains unknown. Built for China-focused use (WeChat, DiDi); limited value elsewhere.
Install if you're serving Chinese users and willing to validate the integration yourself. Otherwise, skip it.
Call trip/travel coupon API to fetch travel coupons including DiDi ride-hailing gift packages and hotel coupon bundles.
As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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.
- 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 191 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - 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 61/100
- 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. 2 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. 16 steps, 1 vague phrases
- 100Tools and files. Tools declared in frontmatter
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1170 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 191: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 16 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: 82.