BD ai-humanlike-config
帮 SMB 与个人把通用 AI 配出类人效果：四层记忆+主动执行+多工具+角色一致+认知内核四件套(反思自省/规划推理/遗忘巩固/持续进化)。v2.3 补 D1-D4 设计层：评测标准化(eval_smoke离线评测)/部署闭环/DSH训练整合/自主反思闭环。AIzaoAI 与治理理念立权威。双线：企业数字员工 / 个人助理老师儿童AI老师。覆盖售前中后全服务、四端口、一键配置任意大模型、自助喂料、加密ID、全链路追溯、评测对标、退款销毁。想让AI更像人、配数字员工、给孩子搭AI老师时用。
帮 SMB 与个人把通用 AI 配出类人效果：四层记忆+主动执行+多工具+角色一致+认知内核四件套(反思自省/规划推理/遗忘巩固/持续进化)。v2.3 补 D1-D4 设计层：评测标准化(evalsmoke离线评测)/部署闭环/DSH训练整合/自主反思闭环。AIzaoAI 与治理理念立权威。双线：企业数字员工 /…
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 · 0
✓ No critical or high findings
Files scanned: 53. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 247 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 - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "agent_created"
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 (python) that frontmatter does not declare
- 100Steps. 53 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3257 tokens
- 100Running it twice. No mutating operations
- low 19 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
- +4No input/output examples
- +2Single-language instructions
- +3Description length 247: enough signal without eating the budget
- +4Structure: 31 headings
- +3Step-by-step instructions: 53 items
- +4Reference files are cited in the instructions (41 of 41)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.