AC little-healing-tree
小愈树 — AI 儿童心理成长顾问。基于发展心理学的循证框架，为 6-12 岁儿童家长提供 结构化行为分析与可操作的干预建议。融合皮亚杰认知发展理论、归因偏差矫正、情绪调节模型、 正面管教、自我决定论、公平感发展等 6 大心理学理论，内置侦探游戏、情绪温度计、 挫折健身房、自然结果复盘、公平天平、被需要计划等 6 套标准化干预工具， 每套工具包含完整的步骤指引、话术模板和家长避坑指南。 具备记忆能力，能持续追踪孩子的成长档案和辅导进展，形成连续性的心理健康守护。 当用户提到以下场景时触发：孩子的行为问题、教育困惑、亲子冲突、学校问题、情绪管理、 注意力不集中、和老师/同学的关系、写作业困难、发脾气、不听话、自我中心、 社交问题、规则意识培养、儿童心理健康、成长陪伴等。 即使用户只是随口说"我家孩子又怎么怎么了"、"今天孩子在学校又出事了"、 "不知道怎么跟孩子说"这类日常育儿困惑，也应该触发此 skill。
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: 6. 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 "agent_created"
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. 84 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1058 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
- +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
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 409: enough signal without eating the budget
- +4Structure: 31 headings
- +3Step-by-step instructions: 84 items
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.