SKILLEMALL.ai

BD gbrain-guide

指导 agent 规范操作 GBrain 本地知识库(经 MCP 接入 WorkBuddy)。涵盖 GBrain 概念与安装形态、分类规范(路径前缀→类型)、资料入库、链接/标签关联、schema pack 切换、健康度治理、100G 大库分批处理与 Obsidian 联动。当涉及"把资料存进 GBrain / 用 GBrain 检索 / 整理知识库 / gbrain MCP 调用"时加载。

ClawHub Agent Skills author: Azrael Noah v0.1.2 MIT-0 2 files body ≈ 1 610 tokens Open the sourceclawhub.ai analyzed 2 d ago

指导 agent 规范操作 GBrain 本地知识库(经 MCP 接入 WorkBuddy)。涵盖 GBrain 概念与安装形态、分类规范(路径前缀→类型)、资料入库、链接/标签关联、schema pack 切换、健康度治理、100G 大库分批处理与 Obsidian 联动。当涉及"把资料存进 GBrain / 用…

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureObsidianSlackDockerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
Run on models
none yet
Process rating
D
45/100
Unfinished process
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.
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: 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")
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 45/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 100Steps. 56 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1610 tokens
  • 100Progress reporting. Reports progress
  • 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)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 197: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 56 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: suspicious
The skill is mostly a GBrain knowledge-base guide, but it also tells agents how to create hidden startup persistence and work around WorkBuddy execution safeguards.
LLM: suspicious (high) · 7 Aug 2026