SKILLEMALL.ai

AB interviewer-claw

Conducts rigorous, structured interviews to stress-test a plan, design, or idea by walking every branch of the decision tree until reaching shared understanding. Use when user says "grill me", "stress-test my plan", "poke holes in this", "interview me about my design", "challenge my assumptions", or "help me think through this".

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 5 files body ≈ 5 072 tokens Open the sourcegithub.com analyzed 2 d ago

Conducts rigorous, structured interviews to stress-test a plan, design, or idea by walking every branch of the decision tree until reaching shared…

As a process B 75/100 · Nearly there — weak spots: result and completion

ProcedureOperations and projectstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
B
75/100
Nearly there
Result and completion w 14
40
When it triggers w 12
50
Steps w 15
60
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5072 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 75/100

  • 40Result and completion. Does not say what the result is
  • 50When it triggers. No condition that starts the skill
  • 60Steps. 141 steps, 7 vague phrases
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5072 tokens
  • 100Tools and files. No external tools needed
  • 100Failures and branches. 6 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress

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 6 example trigger phrases
  • +3Description length 330: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 141 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

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