AC elon-review
Use when reviewing product, strategy, hiring, execution, operations, prioritization, org design, manufacturing/process, or messaging decisions through an Elon Musk-inspired first-principles lens grounded in The Book of Elon. Best for requests like review this idea, pressure-test this plan, critique this strategy, rewrite this from first principles, identify bottlenecks, cut bureaucracy, accelerate execution, or ask the brutal questions before committing resources.
Use when reviewing product, strategy, hiring, execution, operations, prioritization, org design, manufacturing/process, or messaging decisions through an Elon…
As a process C 54/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches
How to improve
- 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
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 54/100
- 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. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (elon-review) differs from the folder (elon-hardcore)
- 60Result and completion. Output format stated, no completion criterion
- 100Tools and files. No external tools needed
- 100Steps. 39 steps
- 100Execution cost. Instruction body is 808 tokens
- low The response is described with custom markup (5 tags): a typed call is more reliable
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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 468: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 39 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.