SKILLEMALL.ai

BC memory-fortress-pro

记忆堡垒专业版是在免费版基础上的全功能升级,为AI Agent包含完整记忆系统。采用六层架构(热内存/温存储/冷存储/归档/云备份/自发提取),基于WAL协议确保持久化。专业版解锁向量语义搜索、Mem0自发提取、云备份三大高级功能,达成跨设备同步与智能记忆管控。Use when 需要AI模型调用、智能对话、Agent编排、LLM应用时使用。不适用于需要100%确定性的关键决策。 功能涵盖: fortress。 功能涵盖: memory。

ClawHub Hermes author: 天轰穿 v1.0.0 MIT-0 2 files body ≈ 6 016 tokens Open the sourceclawhub.ai analyzed 2 d ago

记忆堡垒专业版是在免费版基础上的全功能升级,为AI Agent包含完整记忆系统。采用六层架构(热内存/温存储/冷存储/归档/云备份/自发提取),基于WAL协议确保持久化。专业版解锁向量语义搜索、Mem0自发提取、云备份三大高级功能,达成跨设备同步与智能记忆管控。Use when…

As a process C 52/100 · 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
C
52/100
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

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 220 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning body-long SKILL.md body ≈ 6016 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "edition"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "pricing_tier"

Process rating: all ten parameters 52/100

  • 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
  • 70Execution cost. Instruction body is 6016 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 109 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. No mutating operations
  • low 45 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
  • +2Single-language instructions
  • +3Description length 220: enough signal without eating the budget
  • +4Structure: 111 headings
  • +3Step-by-step instructions: 109 items
  • +4Has examples (24 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This skill is mostly a memory tool, but it asks for broad file and shell authority while also encouraging automatic memory capture, cloud sync, and unrelated system administration actions.
LLM: suspicious (high) · 18 Aug 2026