SKILLEMALL.ai
RU Sign in

BC memory-layered

为 AI agent 建立持久、可检索、可遗忘的六层记忆体系。不是堆更多 context——是把记忆按信息密度分层：L1 对话流、L2 索引（≤200行）、L3 主题文件、L4 技能固化、L5 状态追踪、L6 经验累积。含 REM 做梦（只读扫描发现模式）、SWS 巩固（写入长期记忆）、遗忘脚本（自动清理过期条目）、优雅降级策略。适合需要跨 session 记住用户偏好和项目状态的 agent。

ClawHub Hermes author: Hanyuan v0.1.0 MIT-0 2 files body ≈ 496 tokens Open the sourceclawhub.ai↗ analyzed 20 h ago

为 AI agent 建立持久、可检索、可遗忘的六层记忆体系。不是堆更多 context——是把记忆按信息密度分层：L1 对话流、L2 索引（≤200行）、L3 主题文件、L4 技能固化、L5 状态追踪、L6 经验累积。含 REM 做梦（只读扫描发现模式）、SWS…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedurePersonal productivitytype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
C
53/100
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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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 199 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "skillType"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 496 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 199: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: clean
This is a disclosed local memory-management prompt skill, but users should understand it may store personal and project details in local files.
LLM: benign (high) · VirusTotal: · 21 Jun 2026