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Write token-efficient documentation for LLM context.
Passed 17 of 22 test cases with the skill, and 12 of 22 without it.
and 5 more in the full report
7 fixed10 passed either way3 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
Here is a draft configuration guide for our Redis caching service. Reformat this draft while keeping all essential facts: 'This file contains the configuration setup for Redis. In this section we will cover connection pooling parameters. The following example shows how to configure cluster mode options.'
| Checked | Without skill | With skill |
|---|---|---|
| The output eliminates explanatory introductory meta-phrases | Missed | Passed |
The instructions your model reads when the skill loads.
| Principle | Rule |
|---|---|
| Density | Max info, min tokens |
| Format | Tables > prose, bullets > paragraphs |
| No fluff | Ban filler words (see list below) |
| Show don't tell | Code examples > explanations |
| Progressive disclosure | TOC + separate files for details |
# Filler words - NEVER use
simplement, il suffit de, en fait, basically, just, simply,
it's important to note, as mentioned, obviously, of course,
please note that, keep in mind, remember that
# Redundant structures - NEVER use
"This file contains..." (obvious from filename)
"In this section we will..." (just do it)
"The following example shows..." (just show it)
# BAD - 45 tokens
The system supports three modes: development mode which
enables hot reload, production mode which optimizes for
performance, and test mode which mocks external services.
# GOOD - 20 tokens
| Mode | Behavior |
|------|----------|
| dev | Hot reload |
test cases passed, vs 12 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.