BD continuous-learning
持续学习套件 - AI自主记忆管理工作流：自动识别新任务、记录对话到MemPalace、定期做梦分析、提取精华到文档、自我纠错改进。触发词："持续学习"、"记忆管理"、"自我改进"、"学习体系"。
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: ClawHub
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 · 3
✓ No critical or high findings
Medium and low: 3
-
low Dangerous commands
cmd-cron-mentionREADME.md:252Mentions editing / listing crontabcrontab -l
-
low Dangerous commands
cmd-cron-mentionsetup/install_cron.py:177Mentions editing / listing crontab (string literal in code, not executed)print(" crontab -l")code literal -
low Dangerous commands
cmd-cron-mentionSKILL.md:378Mentions editing / listing crontabcrontab -l | grep openclaw
Files scanned: 11. 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 "dependencies"
Process rating: all ten parameters 41/100
- 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 (continuous-learning) differs from the folder (continuous-learning-kit)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 59 steps
- 100Execution cost. Instruction body is 1585 tokens
- 100Running it twice. No mutating operations
- low 12 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)
- +3Description length 98: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -219 emoji in the instructions: noise for the model
- +2Single-language instructions
- +4Structure: 39 headings
- +3Step-by-step instructions: 59 items
- +4Has examples (21 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.
External checks
ClawHub: suspicious
This is a disclosed continuous-memory skill, but it needs Review because it can keep broad long-term chat memory, run scheduled background jobs, send memory contents to MiniMax, and update core agent files without strong consent or review controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026