BC matchmaker
AI Matchmaker powered by real social media data. Two people scan their accounts — AI cross-analyzes interests, values, lifestyle, aesthetics, and social habits to generate a "Compatibility Report" with match score, chemistry points, friction warnings, and date suggestions. Like astrology but with data. 用真实社交数据算姻缘。两个人各扫一遍社交账号，AI 交叉分析兴趣、三观、生活方式、审美、社交习惯，生成一份「匹配报告」：匹配分数、化学反应点、摩擦预警、约会建议。像算命，但用的是数据。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "depends"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 48 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1531 tokens
- 100Running it twice. No mutating operations
- low 11 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
- -227 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 396: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 48 items
- +4Has examples (11 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.