AD alter-know-yourself
Use when a person wants to see what ~alter knows about them and why, or wants to correct it. Covers setting up your identity so traits are substantiated from what you actually do, reading your own trait movement over time, seeing the evidence trail behind each reading and which projection rule produced it, controlling who is allowed to make claims about your competence, and contesting a reading you disagree with. Trigger phrases include "what does alter know about me", "why does alter think that", "show my evidence trail", "who has vouched for me", "that reading is wrong", "contest this", "set up my alter identity", "how do I strengthen my identity".
Covers setting up your identity so traits are substantiated from what you actually do, reading your own trait movement over time, seeing the evidence trail…
As a process D 41/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions
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
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 41/100
- 0Steps. Prose only: no discrete steps
- 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
- 30Running it twice. 4 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1484 tokens
- 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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +3Description length 658: enough signal without eating the budget
- +4Structure: 9 headings
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.