Academic Literature Search

SkillSearch

ALWAYS use for ANY request to find academic papers - "find papers on X", "what does the literature say about X", "is there research on this", "who has written about X", "find me cites for this claim", "literature search", "any papers in the journals I like", "top journals only", "recent work on X", "has anyone studied this". Use proactively before answering an empirical or doctrinal question from memory, and never run scholar/consensus/paperpile by hand in sequence - this skill parallelizes them. NOT for open-web report writing (deep-research).

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Academic Literature Search skill

What this skill tells your AI

The instructions your AI receives, as published by edwinhu/workflows in skills/research/SKILL.md and read by ahel’s review.

What this skill carries — grep references/ for any subject the names below miss: !d=${CLAUDE_SKILL_DIR}; command -v skill-toc >/dev/null 2>&1 && exec skill-toc "$d"; s=$HOME/.claude/skills/plugin-utils/bin/skill-toc; [ -x "$s" ] && exec "$s" "$d"; echo "(skill-toc unavailable: references and scripts are NOT listed here — install the plugin-utils plugin, or start a new session so its bin/ reaches PATH)"

Multi-source academic search with deduplication, DOI resolution, and journal filtering.

Always read ${CLAUDE_PLUGIN_ROOT}/references/trusted-journals.local.md before presenting results.

IRON LAW: Always Use the Script

NEVER run the sources manually in sequence. ALWAYS use the research script. This is not negotiable.

uv run python3 "${CLAUDE_SKILL_DIR}/scripts/research.py" "<query>" [--n 50] [--min-citations N]

The script parallelizes all sources and DOI resolution automatically. Doing it manually serializes everything and triples wall time.

Sources

SourceToolStrengthDefault
scholar lookupKeyword/citation-rankedFinance classics, foundational papers
consensus CLIEmpirical corpus, sorted by citationsAccounting/finance empirical literature; law reviews (T14 flagships are indexed)
Paperpile bibPersonal library (My Library.bib)Papers already in your collection
scholar searchNL semanticConceptual literature, unindexed specialty reviewsopt-in (--scholar-search)

scholar search is opt-in because it shares rate limits with scholar lookup and 429s when run in parallel. Add --scholar-search when you specifically want semantic/NL results.

Trusted-journal filtering

--journals-only restricts the consensus source server-side to the journals listed in ${CLAUDE_PLUGIN_ROOT}/references/trusted-journals.local.md (one exact name per line, # comments). Use it whenever the user asks for "journals I like", "relevant journals only", or "top journals" — it returns --n trusted papers instead of an unfiltered set that collapses to a handful once you mark ★.

The other sources are unaffected: scholar and the Paperpile bib still run unfiltered, so the union stays broad. To add a journal, verify the exact indexed name with ~/projects/consensus-cli/consensus journals "<partial>" before appending it — an unindexed name matches nothing, silently.

Output Schema

The script outputs a JSON array. Each paper has:

{
  "title": "...",
  "authors": ["..."],
  "year": 2023,
  "journal": "...",           // original journal label (may be SSRN)
  "journal_resolved": "...",  // CrossRef-resolved journal (present if SSRN label was resolved)
  "doi": "...",
  "citations": 150,
  "takeaway": "...",
  "url": "...",
  "sources": ["lookup", "consensus"]  // all sources that returned this paper
}

LLM Review Step (After Script)

After running the script, read ${CLAUDE_PLUGIN_ROOT}/references/trusted-journals.local.md and cross-reference each paper's effective journal (use journal_resolved if present, else journal) against the trusted list:

  • ★ = journal matches trusted list
  • Papers in sources: ["lookup", "consensus"] (multiple sources) = higher confidence
  • Papers from bib source = already in user's library (flag with 📚)

Presentation Format

★ [Title](url) — Authors (Year), *Journal*, N citations  [sources]
  > Takeaway: ...

📚 ★ [Title](url) — Authors (Year), *Journal*  [in your library]
  > Takeaway: ...

Trusted papers first (sorted by citations desc), then non-trusted in a collapsed table.

Red Flags

  • About to run the sources manually in sequence → STOP. That serializes the work and triples wall time; run uv run python3 research.py "<query>".
  • About to call mcp__consensus__search → STOP. It is rate-limited to 3 results; the script uses the CLI binary automatically.
  • About to present results before reading trusted-journals.local.md → STOP. The ★ trusted-journal signals come from that file; read it first, always.
  • User asked for their journals only, and you ran unfiltered then dropped most results → STOP. Pass --journals-only; it filters server-side so all --n results count.
  • About to append a journal to trusted-journals.local.md without verifying it → STOP. consensus journals "<partial>" first; a wrong name fails silently.
  • About to use the journal field when journal_resolved is present → STOP. The SSRN label hides the real venue; always prefer journal_resolved.

Common Patterns

# Standard search
uv run python3 "${CLAUDE_SKILL_DIR}/scripts/research.py" "mandatory disclosure"

# With citation floor
uv run python3 "${CLAUDE_SKILL_DIR}/scripts/research.py" "poison pill" --min-citations 50

# Trusted journals only (server-side filter on the consensus source)
uv run python3 "${CLAUDE_SKILL_DIR}/scripts/research.py" "board independence" --journals-only

# More results from Consensus
uv run python3 "${CLAUDE_SKILL_DIR}/scripts/research.py" "corporate governance" --n 100

# Disable streaming (wait for all sources, output pretty-printed JSON)
uv run python3 "${CLAUDE_SKILL_DIR}/scripts/research.py" "mandatory disclosure" --no-stream

Streaming Mode (default)

Without --stream, the script waits for all four sources before emitting anything — Consensus takes ~60s, so fast sources (bib <1s, Scholar ~10s) sit idle.

With --stream, the script emits one NDJSON line per event as it happens:

{"event": "source", "source": "bib", "papers": [...]}
{"event": "source", "source": "scholar-lookup", "papers": [...]}
{"event": "source", "source": "scholar-search", "papers": [...]}
{"event": "source", "source": "consensus", "papers": [...]}
{"event": "final", "papers": [...]}
  • source events: raw papers from each source as it completes (may have duplicates across sources)
  • final event: deduplicated + CrossRef-resolved unified set

Process source events as they arrive to present early results; use final for the complete deduplicated list. Pass --no-stream for batch mode (pretty-printed JSON after all sources complete).

Signals

GitHub stars
21
Forks
4
Last commit
Sep 2026
Hacker News mentions
20

ahel review

  • K6low
    bundled executables the agent is told to run

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Catalog kind
skill
Gateway key
research-edwinhu
Source
github.com/edwinhu/workflows