paper-search-pro

paper-search-pro

Multi-source literature search with adjustable depth. Four tiers, five data sources orchestrated by you (the main agent). Python helpers handle deterministic work; LLM classification is delegated to parallel Inline SubAgents — no external API key required.

When to use this skill

• User wants to find academic papers / 找文献 / 论文搜索
• User is preparing a literature review, systematic review (SR), scoping review, or meta-analysis
• User wants to scope research on a topic for a thesis / proposal / coursework / news story
• User asks "what research exists on X" / "find me papers about Y"
• User uploads a query that suggests literature gathering (PICO, SPIDER, MeSH, RCT, etc.)

When NOT to use

• User wants to read a specific paper (use PDF reader / download tool)
• User wants to summarize a single known paper (use a summarizer)
• User wants to download PDFs given DOIs (use paper-downloader-portable)
• User already has a literature set and wants to write a review (use literature-set-review / factor-outcome-review)
• User wants concept explanation, not papers ("what is prospect theory" → just answer)

🔥 Execution discipline (read this BEFORE running anything)

These four rules govern every step below. Violating them is the dominant failure mode observed in real sessions — re-read them whenever you feel rushed.

Rule A — NEVER cd into the Skill directory

Reason: cd $PSP_HOME rebinds ./ to the Skill asset directory. Every ./paper-search-results/... after that lands inside the Skill folder, not where the user is working. Re-installing the Skill overwrites history; the user can't find outputs in their own working directory.

Correct pattern — execute helpers from the user's working directory using PYTHONPATH:

PYTHONPATH=$PSP_HOME \
  python3 -m scripts.openalex_helper search "<query>" --limit 30 \
  > "$SEARCH_DIR/raw/openalex.json"

Where $PSP_HOME is the Skill install directory (resolved in STEP 0) and $SEARCH_DIR is an absolute path under the user's PWD (also from STEP 0). Shell cwd remains the user's PWD; ./ paths resolve to where the user expects.

Rule B — Parallelism is MANDATORY for SubAgent dispatch

When you launch classifier SubAgents (STEP 6), you must put up to 5 Task tool_use blocks inside one assistant message. Serial dispatch (one Task per message, waiting for each result) makes Standard tier take ~17 min instead of ~10. See STEP 6 worked example.

Rule C — Tell the user every time you skip a step

If you deliberately skip any STEP (because tier budget is exhausted, data is empty, or user preference), state it explicitly:

• What you skipped (e.g. "STEP 10 L3 enrichment")
• Why (tier? data? user choice?)
• What's lost (e.g. "no influentialCitationCount, no funder/license fields")
• How to recover (e.g. "re-run at --tier deep to include this")

Never skip silently. Skipping is fine; surprising the user is not.

Rule D — Read the cited references/ file BEFORE the step

Each STEP names a references/<file>.md. Read it before running the step's commands — the cheatsheets contain edge cases that are not duplicated in SKILL.md. Average must-read coverage across recent sessions was 5/17 — drive it higher.

Architecture at a glance

You (main agent) drive the workflow per this SKILL.md.
Python helpers do deterministic work — NO LLM inside, NO external API key.

  L1 OpenAlex (primary)  → deep top-100 multi-strategy
  L2 PubMed (medical)    → MeSH enricher (mostly; Audit-tier can search independently)
  L2 arXiv (CS/preprint) → T-0~T-4 freshness sentinel
  L3 Semantic Scholar    → influentialCitationCount + abstract fallback
  L3 CrossRef            → funder / license / clinical-trial-number

  Classification         → Inline SubAgents (parallel, file-IPC, 5 per message)
  Output                 → HTML (Shadcn) + MD + BibTeX/RIS/CSV + PRISMA-S log

The 4 tiers — pick first

| Tier | Wall-clock | Papers | When to pick | |------|------------|--------|--------------| | Quick | ~5-8 min | 20-60 | "查一下" / "几篇" / "before tomorrow" / fast scope | | Standard (default) | ~10-17 min | 60-180 | Scope a topic / write background / general lit search | | Deep | ~30-45 min | 180-400 | "thorough" / writing a review article / 综述写作 | | Audit | ~2-3 hr | 400-1000+ | "systematic review" / "PRISMA" / "Cochrane" / "meta-analysis" |

📖 BEFORE picking, read references/tier_decision.md. Tell the user your choice and why. For Audit, show limitations warning + get explicit confirmation before starting.

The recipe

For every literature search, follow these steps in order. Each step references a references/ file for details. Skip files only when the step is obviously trivial for the case at hand — and announce the skip per Rule C.

STEP 0 — Setup ($PSP_HOME + working directory)

📖 BEFORE THIS STEP, read: references/setup.md.

Resolve the Skill install path into $PSP_HOME — every later step uses PYTHONPATH=$PSP_HOME. The Skill ships as a SKILL.md package; different Agents install it at different paths (~/.claude/skills/, ~/.codex/skills/, ~/.agents/skills/, ~/.config/opencode/skills/, project-local .claude/skills/, etc.). Resolve $PSP_HOME once via a three-layer chain — explicit injection first, env var second, filesystem fallback third — and reuse it in every helper invocation.

# Layer 1: explicit injection. If you (the agent) already know where this
#          SKILL.md lives — because your harness exposed its absolute path —
#          substitute it here and skip Layers 2-3:
#   export PSP_HOME="<absolute directory containing this SKILL.md>"
#
# Layer 2: agent-injected env var (Claude Code / CodeBuddy populate these).
# Layer 3: walk the known cross-agent install locations.

PSP_HOME="${PSP_HOME:-${CLAUDE_SKILL_DIR:-${CODEBUDDY_SKILL_DIR:-}}}"
if [ -z "$PSP_HOME" ]; then
  for d in \
    "$HOME/.claude/skills/paper-search-pro" \
    "$HOME/.codex/skills/paper-search-pro" \
    "$HOME/.agents/skills/paper-search-pro" \
    "$HOME/.config/opencode/skills/paper-search-pro" \
    "$HOME/.codeium/windsurf/skills/paper-search-pro" \
    "$HOME/.config/goose/skills/paper-search-pro" \
    "$HOME/.cline/skills/paper-search-pro" \
    "$HOME/.roo/skills/paper-search-pro" \
    "$HOME/.copilot/skills/paper-search-pro" \
    "./.claude/skills/paper-search-pro" \
    "./.codex/skills/paper-search-pro" \
    "./.agents/skills/paper-search-pro" \
    "./.cursor/skills/paper-search-pro" \
    "./.opencode/skills/paper-search-pro" \
    "./.windsurf/skills/paper-search-pro"; do
    [ -f "$d/SKILL.md" ] && PSP_HOME="$d" && break
  done
fi
[ -z "$PSP_HOME" ] && { echo "ERROR: paper-search-pro install not found. Set PSP_HOME to the directory containing SKILL.md."; exit 1; }
export PSP_HOME
echo "Using Skill install: $PSP_HOME"

Verify config keys (executed from any cwd, never cd into the Skill dir):

PYTHONPATH=$PSP_HOME python3 -c \
  "from scripts.config import load_config; c = load_config(); print('OK' if c.openalex_api_key and c.ncbi_email else 'MISSING — see references/setup.md')"

If "MISSING", point the user to references/setup.md (5 keys, all free, ~15 min total) and halt.

Set up the working directory variable — every subsequent step uses $SEARCH_DIR:

SEARCH_ID="<topic_slug>_<tier>_$(date +%Y%m%d_%H%M%S)"   # e.g. clt_education_quick_20260522_103045
SEARCH_DIR="$(pwd)/paper-search-results/$SEARCH_ID"
mkdir -p "$SEARCH_DIR/raw" "$SEARCH_DIR/batches" "$SEARCH_DIR/classifications"
echo "Outputs will land in: $SEARCH_DIR"

$SEARCH_DIR is now an absolute path under the user's PWD. Use "$SEARCH_DIR/..." (quoted, with the variable) in every helper command below — not ./paper-search-results/....

STEP 1 — Plan the query (MANDATORY for all tiers)

📖 BEFORE THIS STEP, read: references/query_planner.md.

**Detect query lang