SKILLEMALL.ai

BD dse-loop

Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says "DSE", "design space exploration", "sweep parameters", "optimize", "find best config", or wants iterative parameter tuning.

wanshuiyin/Auto-claude-code-research-in-sleep Claude Code author: wanshuiyin MIT 1 file body ≈ 3 392 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Autonomous design space exploration loop for computer architecture and EDA.

As a process D 43/100 · Unfinished process — References files that are not bundled: ../shared-references/external-cadence.md

ProcedureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
95
Quality 40%
83
Run on models
none yet
Process rating
D
43/100
Unfinished process
References files that are not bundled: ../shared-references/external-cadence.md
Tools and files w 18
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. The text references files that are not there: add them or drop the references.
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
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash(*)
    allowed-tools: Bash(*) Read Grep Glob Write Edit

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../shared-references/external-cadence.md

Process rating: all ten parameters 43/100

Will not run. References files that are not bundled: ../shared-references/external-cadence.md
  • 0Tools and files. 1 referenced file(s) missing: ../shared-references/external-cadence.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 5 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 55Failures and branches. 1 branches
  • 85Steps. 72 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3392 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 318: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 72 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.