SKILLEMALL.ai

BB sdw-kb

any input (code, docs, papers, images) → knowledge graph → clustered communities → HTML + JSON + audit report. Uses graphifyy via uv tool environment. Trigger whenever the user mentions knowledge graphs, graphify, sdw-kb, or wants to turn files/code/docs into a navigable knowledge graph, even if they don't explicitly say "sdw-kb".

ClawHub Agent Skills author: yangxiaoqiang1992 v1.0.0 MIT-0 2 files body ≈ 9 139 tokens Open the sourceclawhub.ai analyzed 2 d ago

any input (code, docs, papers, images) → knowledge graph → clustered communities → HTML + JSON + audit report.

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, execution cost

IntegrationSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
99
Quality 40%
69
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
30
Execution cost w 6
40
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-password-literal SKILL.md:656
    Hard-coded password / key literal (may be an example)
    result = push…o4j(G, uri='NEO4J_URI', user='NEO4J_USER', password='NEO4…ORD', communities=communities)

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 9139 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "trigger"

Process rating: all ten parameters 65/100

  • 0Result and completion. Does not say what the result is
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 40Execution cost. Instruction body is 9139 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (bash, web, git, python, node) that frontmatter does not declare
  • 85Steps. 48 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 6 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (11 tags): a typed call is more reliable

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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +3Description length 332: enough signal without eating the budget
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 48 items
  • +4Has examples (31 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
This skill has a coherent knowledge-graph purpose, but it can persistently index local content and offers network, server, watch, and remote database modes with broad activation and limited guardrails.
LLM: suspicious (high) · VirusTotal: · 11 Jun 2026