BD neural-memory
神经记忆系统 — 使用传播激活的联想记忆，实现持久、智能的回忆。主动使用场景：(1)需要跨会话记住事实、决策、错误或上下文 (2)用户问"你还记得..."或引用过去对话 (3)开始新任务时注入相关上下文 (4)做出决策或遇到错误后存储供将来参考 (5)用户问"为什么X发生？"通过记忆追踪因果链。
As a process D 49/100 · 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 the model run — optional
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Unexpected scalar at node end at line 2, column 84: …忆。主动使用场景：(1)需要跨会话记住事实、决策、错误或上下文 (2)用户问"你还记得..."或引用过去对话 (3)开始新任务时注入相关上下文 (4)做出决… ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "keywords"
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (neural-memory) differs from the folder (maske-neural-memory)
- 100Tools and files. No external tools needed
- 100Steps. 15 steps
- 100Execution cost. Instruction body is 702 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
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 148: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.
External checks
ClawHub: suspicious
This is a disclosed persistent-memory skill, but it defaults to saving and reusing conversation details without clear consent, retention, deletion, or sensitive-data limits.
LLM: suspicious (high) · VirusTotal: · 29 May 2026