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AI-powered paper summary and search. Import of literature-engine/literature-search skill. AI summary level — cite as "AI-extracted" not "paper states".
Passed 22 of 25 test cases with the skill, and 14 of 25 without it.
and 5 more in the full report
8 fixed14 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
When running a literature search strategy for sparse mixture-of-experts models, how is a single execution unit defined for budget tracking purposes?
| Checked | Without skill | With skill |
|---|---|---|
| Account for each budget unit as a combination of fetching a paper and generating its corresponding summary | Missed | Passed |
The instructions your model reads when the skill loads.
AI-powered paper summary and search.
Import — strictly follow literature-engine/literature-search skill protocol.
AI summary level — cite findings as "AI-extracted" not "paper states". For authoritative claims about paper content, use paper-research (full text reading).
Quantity target is set by the calling strategy's budget table. This SOP executes one unit = one paper fetch + AI summary generation.
literature-engine repo → skills/literature-search/SKILL.md
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| literature-search | Medium-depth literature search — read AI-summarized reports for every paper analyzed |
test cases passed, vs 14 / 25 without
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