CC lean4-mathlib
Formalizes and checks mathematical statements in Lean 4 with Mathlib, covering the lake project layout and pinned toolchain, `lake exe cache get` before `lake build`, searching Mathlib through Loogle, `exact?`, `apply?` and `simp?`, tactic hygiene, finishing without `sorry`, auditing with `#print axioms`, and making sure the formal theorem statement matches the informal claim exactly. Use when asked to prove, formalize, check or repair a Lean theorem or a Mathlib-based development; use the coq skill for Coq or Rocq, and ordinary mathematical writing for informal proofs.
Formalizes and checks mathematical statements in Lean 4 with Mathlib, covering the lake project layout and pinned toolchain, lake exe cache get before lake…
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Read Write Edit Bash webfetch
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "summary"
Process rating: all ten parameters 51/100
- 0Result and completion. Does not say what the result is
- 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
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 26 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1352 tokens
- high The skill tells the model to perform an irreversible action with no human approval
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)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +3Description length 576: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 26 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.