SKILLEMALL.ai

AC quantum-circuit-builder-with-proof

Quantum Circuit Builder with Proof: Use this product when a quantum circuit needs verifiable evidence, not just. Use when an agent needs quantum circuit builder with proof, formally verified quantum circuit design, proof carrying quantum circuit certificates (qpcert), independent verification of a quantum proof certificate from another party, audit ready quantum computing artifacts for research and compliance, certify circuit, circuit, claims through AgentPMT-hosted remote tool calls.

ClawHub Agent Skills author: AgentPMT v1.0.4 MIT-0 3 files body ≈ 10 806 tokens Open the sourceclawhub.ai analyzed 2 d ago

Quantum Circuit Builder with Proof: Use this product when a quantum circuit needs verifiable evidence, not just.

As a process C 64/100 · Has gaps — weak spots: inputs and preconditions, execution cost, running it twice

AnalyzerAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
64/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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 · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 10806 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 64/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 6 mutating operations with no state check
  • 40Execution cost. Instruction body is 10806 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 90 steps
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 13 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 489: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 90 items
  • +3Output format is stated explicitly
  • +4Has examples (23 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
The skill mostly matches its quantum-circuit purpose, but it needs Review because it delegates authority to live remote instructions and runs submitted Lean code in a shared cloud service without untrusted-code isolation.
LLM: suspicious (high) · 9 Sept 2026