BD 墨池
知识管理技能，自动识别学习行为，智能管理知识库。【始终在线模式】每次对话开始时自动加载， 全程监听用户输入，从任意对话中提取知识点、记录学习行为、更新用户画像。 **全局生效配置**：已在 MEMORY.md 中记录，每次对话自动加载，无需手动触发。 命令：/墨池 画像、/墨池 复习、/墨池 推荐、/墨池 索引、/墨池 搜索、/墨池 统计、/墨池 导出。
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: 18. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
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 (墨池) differs from the folder (inkpot)
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 17 steps
- 100Execution cost. Instruction body is 1077 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
- +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
- +1No license
- +2Single-language instructions
- +3Description length 180: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (14 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.
External checks
ClawHub: suspicious
InkPot is a local knowledge-management skill, but it asks to monitor ordinary conversations, store learning/profile data, and persist auto-loading across future sessions without adequate user controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026