BD AWS架构图生成工具
通过Amazon Q CLI和MCP服务器在GitHub Codespace中快速生成高质量的AWS架构图。
通过Amazon Q CLI和MCP服务器在GitHub Codespace中快速生成高质量的AWS架构图。
As a process D 36/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
IntegrationGitHubKubernetesAWSInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
How to improve
- 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
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 36/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (AWS架构图生成工具) differs from the folder (awslabs-aws-diagram)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 85Steps. 110 steps, 2 vague phrases
- 100Execution cost. Instruction body is 3018 tokens
- low 10 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)
- +3Description length 54: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 15 headings
- +3Step-by-step instructions: 110 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.
External checks
ClawHub: suspicious
This skill is labeled as an AWS diagram generator, but its artifacts require and persist a Xiaobenyang API key and route diagram requests to an external Xiaobenyang service with inconsistent leftover Gaokao references.
LLM: suspicious (high) · VirusTotal: · 3 Jul 2026