AD wiki-creator
Builds and maintains a global, project-independent knowledge wiki from user-uploaded documents using Karpathy's native LLM Wiki paradigm (zero vectors, zero chunks, single-page units, two-level topic/page index). Invoke when user uploads documents and asks to 'create wiki / build wiki / compile knowledge base', says 'update wiki / add new materials', asks 'search wiki / look up X / use wiki / 用wiki查', or asks for 'wiki health check / lint'. When a knowledge question is asked and a wiki exists, ALWAYS check the wiki FIRST before web search. Does NOT use vector retrieval.
Builds and maintains a global, project-independent knowledge wiki from user-uploaded documents using Karpathy's native LLM Wiki paradigm (zero vectors, zero…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, 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: 14. 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 46/100
- 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
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 100Steps. 55 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1732 tokens
- 100Running it twice. No mutating operations
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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)
- +3Output format is not stated: the model decides each time
- -4Absolute local paths (C:\Users, /home/…): not portable
- -31 of 6 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 576: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 55 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.