CD qingtian-psychology-self-study
青田·心理自习室（咨询师实战训练台）。当心理咨询师或准咨询师想要提高、完善、丰富自己的理论与对话实践本领时使用。核心是「练对话」：17 流派 TPR 练习器提供三模式——体验（AI 扮咨询师，感受流派干预）、实操（AI 扮来访者，用户当咨询师施技，可配来访者画像）、督导（贴逐字稿，AI 当督导师做五步分析+五维透镜）。配套理论补课（learn 服务练习）、评估施测演练（21 量表）、个案概念化（cases）、伦理两难决策、反移情记录、成长支持。即用即走：新用户一键默认开跑、一句话可定制，日常只推荐"下一件事"，按阶段推进，阶段总结为完成门槛。能力成长按五维衡量：对话技术/个案概念化/理论功底/评估能力/伦理与自我。始终坚持伦理边界：不诊断、不开药、不替代专业心理咨询，危机情况立即提供求助资源与情绪急救包（单源 resources/crisis-resources.md）。
青田·心理自习室（咨询师实战训练台）。当心理咨询师或准咨询师想要提高、完善、丰富自己的理论与对话实践本领时使用。核心是「练对话」：17 流派 TPR 练习器提供三模式——体验（AI 扮咨询师，感受流派干预）、实操（AI 扮来访者，用户当咨询师施技，可配来访者画像）、督导（贴逐字稿，AI…
As a process D 41/100 · Unfinished process — References files that are not bundled: 徽章
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 80. 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") - warning
body-longSKILL.md body ≈ 5034 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: 徽章 - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 41/100
- 0Tools and files. 1 referenced file(s) missing: 徽章
- 0Result and completion. Does not say what the result is
- 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
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 5034 tokens
- 100Steps. 107 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 14 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 tags): a typed call is more reliable
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
- +2Single-language instructions
- +3Description length 391: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 107 items
- +4Has examples (1 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.