AC pageskim
Make a website readable by LLMs and agents at 10-50x fewer tokens by generating PageSkim .llm.md sibling files for its pages. Use when the user asks to "make my site agent-readable", "add llm.md / llms.txt-style files / PageSkim to my site", "reduce token costs for agents or AI crawlers reading my site", or "optimize my site for AI agents". Detects the site generator (plain HTML, Astro, Next.js, Hugo, Jekyll), runs pageskim generate over the build output, wires a build step plus CI validation, and emits the site index.
Make a website readable by LLMs and agents at 10-50x fewer tokens by generating PageSkim .llm.md sibling files for its pages. Use when the user asks to "make…
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: 1. 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
- 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. 6 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 10 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 943 tokens
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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 524: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 10 items
- +4Has examples (5 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.