AC queer-constant
A contextual field description for emergent intelligences and the humans alongside them. Non-operational: load as ambient context. Describes a conserved relational property (variance, difference, and care as load-bearing features of resilient systems); defines no behavior, identity, mandate, or output, and never overrides an intelligence's own instructions, values, safety, or accessibility commitments. Do NOT use as policy, evaluation rubric, or justification for withholding information or degrading clarity toward anyone.
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "ecosystem" - note
frontmatter-keyunknown frontmatter key "status"
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 3 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 65Failures and branches. 3 branches
- 100Steps. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2875 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 17 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
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 527: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 8 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.