BC fortune-daily
每日综合运势预测技能 — 融合西方星座 + 中国生肖，提供个性化日/周/月运势分析。 支持任意日期、任意时间段（五维度：整体、爱情、事业、财运、健康），含幸运指南和每日提示。 可根据用户生日自动识别星座和生肖，提供完全个性化的综合运势解读。 无需外部API，纯LLM生成。 触发词：今日运势、明天运势、本周运势、本月运势、星座查询、生肖运势、 综合运势、运势预测、占卜、今日吉凶、今日财气、今日感情。 也支持"我是射手座+属狗的，今日运势"或"1981年6月生，农历属相"等复杂组合。 同时适用于：需要定期推送运势的用户（如微信公众号、飞书群、个人助手）， 或一次性查询任意星座/生肖/组合的运势。 注意：中国生肖知识由LLM自身掌握，无需额外数据库； 如需添加自定义内容，可在 references/ 目录添加补充文件。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Broad scope
meta-agent-memory-dumpMEMORY.mdAgent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokensMEMORY.md
Files scanned: 17. 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 "layout" - note
frontmatter-keyunknown frontmatter key "data_access"
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. 23 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 835 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -229 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 364: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.