Require DeepSeek for literature screening
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SKILL.md
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SKILL.md
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@ -14,9 +14,10 @@ structure, properties, mechanism, device/application performance, and limits.
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It can also route through the user's Zotero/Obsidian literature-note workflow:
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It can also route through the user's Zotero/Obsidian literature-note workflow:
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extract keywords from the manuscript topic or draft, use QQnote-generated
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extract keywords from the manuscript topic or draft, use QQnote-generated
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Zotero child notes or paper tables as literature inputs, separate strongly
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Zotero child notes or paper tables as literature inputs, ask DeepSeek to screen
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related and weakly related papers inside QQsci, then use those papers to improve
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those candidate notes into strongly related and weakly related papers under
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positioning, introduction logic, comparison, novelty framing, and citations.
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QQsci's rules, then use those papers to improve positioning, introduction
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logic, comparison, novelty framing, and citations.
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## Core stance
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## Core stance
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@ -123,8 +124,10 @@ DeepSeek/AwesomeGPT Zotero notes generated by QQnote or equivalent sources.
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2. If the target journal is absent, ask the author for it. If they want advice,
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2. If the target journal is absent, ask the author for it. If they want advice,
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open `references/journal-positioning.md` and recommend several tiers.
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open `references/journal-positioning.md` and recommend several tiers.
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3. Open `references/literature-routing.md` and perform QQsci's own relevance
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3. Open `references/literature-routing.md` and perform QQsci's own relevance
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screening against the existing notes or QQnote-generated comparison tables.
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routing against the existing notes or QQnote-generated comparison tables.
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4. Screen notes into:
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The large-scale strong/weak paper screening pass must be run by DeepSeek when
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DeepSeek is configured.
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4. Ask DeepSeek to screen notes into:
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- `strongly related`: same material, same material family plus same device,
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- `strongly related`: same material, same material family plus same device,
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same mechanism, same target journal/neighbor journal, or direct benchmark.
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same mechanism, same target journal/neighbor journal, or direct benchmark.
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- `weakly related`: same direction, adjacent material family, same
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- `weakly related`: same direction, adjacent material family, same
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@ -80,7 +80,8 @@ for QQsci's manuscript reasoning.
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QQsci owns:
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QQsci owns:
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- manuscript keyword extraction
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- manuscript keyword extraction
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- strong/weak related-paper screening
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- DeepSeek screening prompts, rules, and review of strong/weak related-paper
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results
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- target-journal positioning
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- target-journal positioning
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- comparative review against strong papers
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- comparative review against strong papers
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- submission-package audit
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- submission-package audit
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@ -93,4 +94,7 @@ QQnote owns:
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- generating paper comparison tables from Zotero items
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- generating paper comparison tables from Zotero items
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- optional QQnote note-state maintenance when explicitly requested
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- optional QQnote note-state maintenance when explicitly requested
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QQnote output is an input to QQsci, not the decision engine.
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DeepSeek owns the large-scale screening pass over QQnote/Zotero/Obsidian note
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candidates when QQsci needs strong/weak related papers. QQnote output is the
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candidate corpus; QQsci owns the criteria, prompt, sanity check, and downstream
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writing brief.
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@ -44,6 +44,15 @@ Return a query pack:
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## DeepSeek screening brief
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## DeepSeek screening brief
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Strong/weak related-paper screening must be executed with DeepSeek when a
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usable DeepSeek configuration is available. QQsci prepares the rules and inputs;
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DeepSeek reads the QQnote/Zotero/Obsidian note candidates and returns the
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screened set.
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Do not ask Codex to silently classify a large note library from memory. Codex may
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do a small sanity check after DeepSeek returns results, but DeepSeek is the
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screening engine for the note set.
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Give DeepSeek a compact, structured task:
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Give DeepSeek a compact, structured task:
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```text
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```text
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@ -68,6 +77,59 @@ Screen the notes and return:
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4. Do not include papers only because of a broad keyword match.
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4. Do not include papers only because of a broad keyword match.
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```
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```
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## DeepSeek output contract
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Require DeepSeek to return structured Markdown or JSON that can be handed to
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QQsci and then QQwrite:
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```json
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{
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"keyword_pack": {
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"must_match": [],
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"should_match": [],
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"context": [],
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"exclude": []
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},
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"strongly_related_papers": [
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{
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"title": "",
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"year": "",
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"journal": "",
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"doi": "",
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"zotero_key": "",
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"relation_type": "",
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"usable_for": [],
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"why_strong": "",
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"notes_evidence": ""
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}
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],
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"weakly_related_papers": [
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{
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"title": "",
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"year": "",
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"journal": "",
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"doi": "",
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"zotero_key": "",
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"relation_type": "",
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"usable_for": [],
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"why_weak": "",
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"notes_evidence": ""
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}
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],
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"rejected_near_matches": [
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{
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"title": "",
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"doi": "",
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"reason": ""
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}
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],
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"missing_or_uncertain_metadata": []
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}
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```
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If the output will feed QQwrite, QQsci should convert the screened papers into a
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`qqwrite_brief`-style section plan rather than passing raw notes directly.
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## Strong vs weak relation rules
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## Strong vs weak relation rules
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Strongly related:
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Strongly related:
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@ -1,9 +1,9 @@
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#!/usr/bin/env python3
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#!/usr/bin/env python3
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"""Create a manuscript keyword pack and DeepSeek screening prompt.
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"""Create a manuscript keyword pack and DeepSeek screening prompt.
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This helper is intentionally local-config only. It does not call DeepSeek or
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This helper is intentionally local-config only. It prepares a reproducible
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Zotero by itself; it prepares a reproducible prompt that the skill can use with
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DeepSeek prompt for the required screening pass over QQnote/Zotero/Obsidian
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the user's configured note-search route.
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literature notes. It does not call DeepSeek or Zotero by itself.
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"""
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"""
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from __future__ import annotations
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from __future__ import annotations
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@ -81,8 +81,16 @@ Manuscript profile:
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Return:
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Return:
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1. Strongly related papers: same material, same material family plus same device, same mechanism, direct benchmark, or same target-journal positioning.
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1. Strongly related papers: same material, same material family plus same device, same mechanism, direct benchmark, or same target-journal positioning.
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2. Weakly related papers: same direction, adjacent material family, same characterization logic, similar device architecture, or useful writing pattern.
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2. Weakly related papers: same direction, adjacent material family, same characterization logic, similar device architecture, or useful writing pattern.
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3. For each paper: title, year, journal, Zotero key if present, relation type, useful claim/evidence, and why it matters for the manuscript.
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3. For each paper: title, year, journal, DOI, Zotero key if present, relation type, usable_for, useful claim/evidence, and why it matters for the manuscript.
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4. Reject title-only broad keyword matches.
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4. Reject title-only broad keyword matches.
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5. Return rejected near matches and missing/uncertain metadata separately.
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Output JSON keys:
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- keyword_pack
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- strongly_related_papers
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- weakly_related_papers
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- rejected_near_matches
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- missing_or_uncertain_metadata
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"""
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"""
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