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BD diagram-generator

Generates and iteratively edits Mermaid.js and Draw.io diagrams. Supports multimodal context (reading source code, architecture sketches, and documentation).

ClawHub Agent Skills author: kaudata v1.0.2 MIT-0 8 files body ≈ 707 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSoftware developmentInfrastructureWriting and documentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
95
Quality 40%
66
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token package-lock.json:24
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…v5u+YA72…GbR+/RQAQ==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:47
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-j+gKEx…ahh+s1F2HZ+wAce…RkU++ZWQr…uoQ==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:93
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…rvP+yUUf…4tH/iSSo…tEA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:120
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…DmC+EJUz…RN4+0gEx…AvA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:148
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…B4t+D+OBkj…bcE+mWTyvVV7D/zsdE…1Rw==",
    detector

Files scanned: 8. 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 48/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (diagram-generator) differs from the folder (diagramgenerator)
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 65Failures and branches. 3 branches
  • 100Steps. 9 steps
  • 100Execution cost. Instruction body is 707 tokens
  • 100Running it twice. Mutating operations check current state
  • low The response is described with custom markup (7 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
  • +4No input/output examples
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 157: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 9 items

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

External checks

ClawHub: clean
This is a coherent Gemini-backed diagram tool, but users should understand that selected prompts and files are sent to Gemini and saved outputs are managed by an unauthenticated local web server.
LLM: benign (high) · VirusTotal: · 29 May 2026