SKILLEMALL.ai

BB blueprint

Requirements blueprint workflow for transforming vague task descriptions into high-quality, implementation-ready Spec + RFC documents. **Trigger conditions (trigger if ANY is met):** - User asks to "refine/complete/create requirements/spec/RFC" - User asks to "write/draft a specification or technical design" - User provides a task description and asks for requirement analysis or design proposal - User mentions "需求分析", "技术方案", "Spec", "RFC", "需求文档", "蓝图", "blueprint" - User says "帮我想想怎么实现", "这个需求怎么做", "帮我理一下思路", "画个蓝图" - User gives a vague task and wants to "分析一下怎么做", "帮我想想实现方案" - User mentions "功能设计", "技术评审", "方案讨论", "梳理一下", "想清楚再做" - User says "别急着写代码,先想想", "先做个设计", "写个技术方案" **Workflow:** Elicitation → Analysis → Specification → Technical Design → Validation → Implementation

ClawHub Agent Skills author: XadillaX v1.0.0 MIT-0 5 files body ≈ 7 524 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 66/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, consistency

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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
  • 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 body-long SKILL.md body ≈ 7524 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 66/100

  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 40Consistency. Frontmatter name (blueprint) differs from the folder (blueprint-spec)
  • 70Execution cost. Instruction body is 7524 tokens
  • 85Steps. 276 steps, 2 vague phrases
  • 100Tools and files. No external tools needed
  • 100Result and completion. Output format and completion criterion are stated
  • 100Failures and branches. 12 branches, has a failure section
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 24 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +4No input/output examples
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 10 example trigger phrases
  • +3Description length 788: enough signal without eating the budget
  • +4Structure: 71 headings
  • +3Step-by-step instructions: 276 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
This skill is not malicious, but it can move from planning into code changes and tells the agent not to pause once implementation starts, so it needs careful review before use.
LLM: suspicious (high) · VirusTotal: · 29 May 2026