semantic-scholar

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SKILL.md (first lines)

# Semantic Scholar Paper Search

Search topic or paper ID: $ARGUMENTS

## Role & Positioning

This skill is the **published venue** counterpart to `/arxiv`:

| Skill | Source | Best for |
|-------|--------|----------|
| `/arxiv` | arXiv API | Latest preprints, cutting-edge unrefereed work |
| `/semantic-scholar` | Semantic Scholar API | **Published** journal/conference papers (IEEE, ACM, Springer, etc.) with citation counts, venue info, TLDR |

**Do NOT duplicate arXiv's job.** If results contain an `externalIds.ArXiv` field, the paper is also on arXiv — note this but do not re-fetch from arXiv.

## Constants

- **MAX_RESULTS = 10** — Default number of search results.
- **S2_FETCHER** — canonical name `semantic_scholar_fetch.py`, resolved per
  [`shared-references/integration-contract.md`](../shared-references/integration-contract.md) §2
  (Policy D1 — primary + fallback cascade). If unresolved (canonical
  chain exhausted), fall back to the inline Python alternative
  documented in Step 2.
- **DEFAULT_FILTERS** — For general research queries, apply these by default to reduce noise:
  - `--fields-of-study "Computer Science,Engineering"`
  - `--publication-types JournalArticle,Conference`

> Overrides (append to arguments):
> - `/semantic-scholar "topic" - max: 20` — return up to 20 results
> - `/semantic-scholar "topic" - type: journal` — only journal articles
> - `/semantic-scholar "topic" - type: conference` — only conference papers
> - `/semantic-scholar "topic" - min-citations: 50` — only highly-cited papers
> - `/semantic-scholar "topic" - year: 2022-` — papers from 2022 onward
> - `/semantic-scholar "topic" - fields: all` — remove default field-of-study filter
> - `/semantic-scholar "topic" - sort: citations` — bulk search sorted by citation count
> - `/semantic-scholar "DOI:10.1109/..."` — fetch a single paper by DOI

## Workflow

### Step 1: Parse Arguments

Parse `$ARGUMENTS` for directives:

- **Query or ID**: main search term, or a paper identifier:
  - DOI: `10.1109/TWC.2024.1234567`
  - Semantic Scholar ID: `f9314fd99be5f2b1b3efcfab87197d578160d553`
  - ArXiv: `ARXIV:2006.10685`
  - Corpus: `CorpusId:219792180`
- **`- max: N`**: override MAX_RESULTS
- **`- type: journal|conference|review|all`**: map to `--publication-types`
- **`- min-citations: N`**: map to `--min-citations`
- **`- year: RANGE`**: map to `--year` (e.g. `2022-`, `2020-2024`)
- **`- fields: FIELDS`**: override `--fields-of-study` (use `all` to remove filter)
- **`- sort: citations|date`**: use `search-bulk` with `--sort citationCount:desc` or `publicationDate:desc`

If the argument matches a DOI pattern (`10.XXXX/...`), a Semantic Scholar ID (40-char hex), or a prefixed ID (`ARXIV:...`, `CorpusId:...`), skip search and go directly to Step 3.

### Step 2: Search Papers

Resolve `$S2_FETCHER` via the canonical strict-safe chain (see
[`shared-references/integration-contract.md`](../shared-references/integration-contract.md) §2):

```bash
cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills.txt ]; then
    ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null) || true
fi
if [ -z "${ARIS_REPO:-}" ] && [ -f "$HOME/.aris/repo" ]; then
    ARIS_REPO=$(cat "$HOME/.aris/repo" 2>/dev/null) || true
fi
S2_FETCHER=".aris/tools/semantic_scholar_fetch.py"
[ -f "$S2_FETCHER" ] || S2_FETCHER="tools/semantic_scholar_fetch.py"
[ -f "$S2_FETCHER" ] || { [ -n "${ARIS_REPO:-}" ] && S2_FETCHER="$ARIS_REPO/tools/semantic_scholar_fetch.py"; }
[ -f "$S2_FETCHER" ] || S2_FETCHER=""
```

**Standard search** (default — relevance-ranked):

```bash
python3 "$S2_FETCHER" search "QUERY" --max MAX_RESULTS \
  --fields-of-study "Computer Science,Engineering" \
  --publication-types JournalArticle,Conference
```

**Bulk search** (when `- sort:` is specified, or MAX_RESULTS > 100):

```bash
python3 "$S2_FETCHER" search-bulk "QUERY" --max MAX_RESULTS \
  --sort citationCount:desc \
  --fields-of-study "Computer Science" \
  --year "2020-"
```

If `$S2_FETCHER` is empty (Policy D1 cascade), fall back to inline Python using `urllib` against `https://api.semanticscholar.org/graph/v1/paper/search`.

**Recommended filter combos** (from testing):

| Goal | Flags |
|------|-------|
| High-quality journal papers | `--publication-types JournalArticle --min-citations 10` |
| CS/EE papers, recent | `--fields-of-study "Computer Science,Engineering" --year "2022-"` |
| Foundational / high-impact | `search-bulk --sort citationCount:desc --fields-of-study "Computer Science"` |
| Conference papers only | `--publication-types Conference` |

> **Note**: `--venue` requires exact venue names (e.g. "IEEE Transactions on Signal Processing"), not partial matches like "IEEE". Avoid using `--venue` in automated flows — prefer `--publication-types` + `--fields-of-study`.

### Step 3: Fetch Details for a Specific Paper

When a single paper ID is requested:

```bash
python3 "$S2_FETCHER" paper "PAPER_ID"
```

Where PAPER_ID can be:
- DOI: `10.1109/TSP.2021.3071210`
- ArXiv: `ARXIV:2006.10685`
- CorpusId: `CorpusId:219792180`
- S2 ID: `f9314fd99be5f2b1b3efcfab87197d578160d553`

From wanshuiyin/Auto-claude-code-research-in-sleep, MIT.

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