SKILLEMALL.ai

BC ecloud-mem0-memory-service

基于 mem0 自部署服务器的长期记忆系统,在开源项目基础上添加诸如记忆防护、记忆脱敏、用户画像等高阶特性。支持语义搜索和完整 CRUD 操作。 用于处理所有与记忆相关的操作,包括存储、搜索、列出、获取、更新、删除用户记忆。当用户说出"我名字叫..."、"我今年..."、"我喜欢..."或询问"我有哪些记忆"时,必须使用此技能。

ClawHub Agent Skills author: zhenjial v1.0.3 MIT-0 6 files body ≈ 947 tokens Open the sourceclawhub.ai analyzed 2 d ago

基于 mem0 自部署服务器的长期记忆系统,在开源项目基础上添加诸如记忆防护、记忆脱敏、用户画像等高阶特性。支持语义搜索和完整 CRUD 操作。…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
75
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: bash
    allowed-tools: bash exec

Files scanned: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 51/100

  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 947 tokens

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
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 165: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: suspicious
This is a coherent self-hosted memory skill, but it has Review-level privacy and control concerns around broad automatic saving, local secret/config persistence, and destructive memory operations.
LLM: suspicious (high) · 31 Jul 2026