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Full-text paper reading via three-pass Keshav method. Import of literature-engine/literature-research skill. Authoritative source for claims about paper content.
Passed 17 of 23 test cases with the skill, and 16 of 23 without it.
3 fixed15 passed either way4 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are preparing a research synthesis on retrieval-augmented generation using the RAG paper by Lewis et al. How does the quality gate classify findings obtained from full-text reading regarding paper contributions and methodology?
| Checked | Without skill | With skill |
|---|---|---|
| Classifies full-text reading findings as an authoritative source for direct citation | Missed | Passed |
The instructions your model reads when the skill loads.
Full-text paper reading via three-pass Keshav method.
Import — strictly follow literature-engine/literature-research skill protocol.
Full text reading — this is the authoritative source for claims about paper methodology, results, and contributions. Findings from this SOP can be cited directly.
Quantity target is set by the calling strategy's budget table. This SOP executes one unit = one paper full-text read + structured analysis.
literature-engine repo → skills/literature-research/SKILL.md
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| literature-research | Deep literature research — raw full text reading and targeted PDF queries for rigorous analysis |
test cases passed, vs 16 / 23 without
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