BD bazi-engine
四柱八字命理分析智能体。通过引导式交互收集出生信息（姓名、生日（阳历或农历均可）、出生时间、性别、出生地）， 自动排出四柱八字与大运流年，并参照古代命理典籍进行专业分析。输出必须标注古籍出处，保证可追溯、可检验。 适用场景：用户想算八字、看命盘、测运势、查合婚、补五行、看神煞、看流年，或提到"算命/四柱/命理/bazi/fortune"。 即使只提"算命""八字"而未明确说用 skill，也应启用本 skill。
四柱八字命理分析智能体。通过引导式交互收集出生信息（姓名、生日（阳历或农历均可）、出生时间、性别、出生地）， 自动排出四柱八字与大运流年，并参照古代命理典籍进行专业分析。输出必须标注古籍出处，保证可追溯、可检验。…
As a process D 46/100 · Unfinished process — 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.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Secrets in code
secret-high-entropy-tokentools/build_ui.py:66High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)background:url("data:image/png;base64,iVBO…Hn0/FnEz…mk6/mEu+lUe6…viUdetector -
low Secrets in code
secret-high-entropy-tokenui/index.html:36High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)background:url("data:image/png;base64,iVBO…Hn0/FnEz…mk6/mEu+lUe6…viUdetector
Files scanned: 61. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 209 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 100Steps. 72 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1678 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
- +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
- +4No input/output examples
- +2Single-language instructions
- +3Description length 208: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 72 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.