Academic Research

---
name: academic-research
description: "Academic research methodology pack for systematic literature review, citation integrity, and quality evaluation. Covers PRISMA systematic reviews, meta-analysis, PubMed search, literature surveys, and academic writing standards. Use for any academic research, literature review, citation analysis, paper evaluation, or systematic review task."
version: 0.1.0
type: reference-based
keywords: ["学术", "academic", "论文", "paper", "文献", "literature", "meta-analysis", "元分析", "PRISMA", "systematic review", "系统性综述", "PubMed", "文献综述", "学术研究", "科研"]
---

# Academic Research Capability Pack

> Teaches AI agents HOW to do academic research — depth enforcement, citation integrity, quality scoring, and self-evaluation. Derived from ScienceClaw's 629-line SCIENCE.md protocol + ScholarEval rubric + VOYAGER-inspired Reflexion Cycle.
>
> **CONSUMES**: Research question + optional domain constraints (field, date range, databases).
> **PRODUCES**: Evidence-grounded research report + methodology section + citation audit trail + Reflexion Cycle self-evaluation (for non-trivial tasks).

---

## Scope Disambiguation

This pack covers **academic and scientific research methodology**.

**This pack — use when:**
- User asks about 学术/academic/论文/paper/文献/literature tasks
- Systematic or literature reviews, meta-analyses
- Tasks mentioning PRISMA, PubMed, citation analysis, ScholarEval
- Evaluating research quality or scholarly writing

**NOT this pack — defer to `*research` when:**
- Market analysis, technology trend analysis, competitive analysis
- General non-academic "research X" tasks without scientific context
- Business strategy investigation, product analysis

If ambiguous, ask the user: "Is this academic/scientific research or general market/technology research?"

---

## Step 1: Detect Research Task Type

Classify the user's request into one of four tiers. Each tier has a mandatory minimum depth derived from ScienceClaw SCIENCE.md lines 111-121.

| Tier | Signal Keywords | Min Phases | Min Tool Calls | Session Model |
|------|----------------|-----------|---------------|---------------|
| **Quick factual** | "what is", "define", "quick question", single-fact lookup | 1-2 | 3-5 | Single session, no handoff |
| **Literature survey** | "review literature", "survey papers", "what does the research say", "文献综述" | 1-5 | 20-40 | 1-2 sessions with handoff |
| **Comprehensive review** | "comprehensive review", "analyze the field", "综合分析", "学术综合分析" | 1-6 | 40-80 | Epic: 2-3 phases |
| **Systematic review** | "systematic review", "meta-analysis", "PRISMA", "系统性综述", "元分析" | 1-6 (iterated) | 80+ | Epic: 4-6 phases (PRISMA pipeline) |
| **Multimodal research** | user uploads image, "pattern analysis", "visual comparison", "artifact image", "图像分析", "纹样" | 1-5 | 20-40 | 1-2 sessions; load multimodal-research.md + pattern-extraction.md |

**Example inputs per tier:**

Quick factual:
- "What is the current impact factor of Nature Medicine?"
- "Who first described CRISPR-Cas9 gene editing?"
- "What is the sample size formula for a two-arm RCT?"

Literature survey:
- "Survey recent papers on transformer architectures for protein folding"
- "What does the literature say about remote work productivity?"
- "Review papers on CRISPR cancer therapy from 2023-2025"

Comprehensive review:
- "Analyze the field of large language models for drug discovery"
- "Comprehensive review of causal inference methods in economics"
- "Review all approaches to federated learning in healthcare"

Systematic review:
- "Conduct a systematic review of CBT interventions for anxiety"
- "PRISMA-compliant meta-analysis of statin efficacy in primary prevention"
- "Systematic review of AI diagnostic accuracy in radiology"

Multimodal research:
- "Analyze this image of a ceramic bowl — describe the ornamental pattern and classify the motif types"
- "Compare the palmette designs across these three artifacts from different cultures"
- "Extract the visual features from this food plating photograph for sensory evaluation research"

> Source: Adapted from SCIENCE.md lines 111-121, adjusted per tad-mapping-blueprint.md Decision 6

---

## Step 2: Load References by Task Type

### Protocol References (always applicable)

| Tier | Protocol References |
|------|----------------------|
| Quick factual | zero-hallucination.md only |
| Literature survey | research-protocol.md + zero-hallucination.md + fallback-chains.md |
| Comprehensive review | ALL protocol references + relevant cluster references |
| Systematic review | ALL protocol + ALL cluster references |

### Cluster References (load by research domain)

Load the cluster references that match the research topic. Multiple clusters may apply.

| Research Domain Signal | Load These Cluster References |
|----------------------|------------------------------|
| Literature search, citation analysis | references/literature-search.md |
| Academic database queries (general) | references/database-apis-general.md |
| Life science databases (protein, gene, drug) | references/database-apis-life-sciences.md |
| Statistical analysis, meta-analysis | references/statistics.md |
| Paper/grant/report writing | references/writing.md |
| Figures, plots, charts | references/visualization.md |
| Biomedical / life science domain | references/domain-biomedical.md |
| Physical / computational science | references/domain-physical.md |
| Social science / economics | references/domain-social.md |
| Experiment design, ethics, reproducibility | references/experiment-design.md |
| Image analysis, visual evidence, multimodal | references/multimodal-research.md |
| Ornamental patterns, motifs, cross-cultural visual comparison | references/pattern-extraction.md |
| Quantitative image measurement, CV tools, similarity scoring, frequency analysis | references/quantitative-analysis.md |

Read the loaded reference files and apply their rules during research execution.

---

## Step 3: Alex/Blake Role Mapping for Research Tasks

| Research Activity | Alex (Design) | Blake (Execute) |
|-------------------|---------------|-----------------|
| Research question formulation | Elicits via Socratic Inquiry | — |
| Search strategy + database selection | Specifies in handoff | — |
| Search execution | — | Runs curl/API commands |
| Paper reading + extraction | — | Reads and extracts findings |
| Quality assessment | Defines criteria in handoff ACs | Applies ScholarEval from scholar-eval.md |
| Synthesis across sources | — | Synthesizes with citation audit |
| Report writing | — | Writes report with methodology section |
| Depth enforcement | Sets minimum tier in handoff | Follows research-protocol.md thresholds |
| Citation integrity | AC: "every citation traces to tool result" | Self-checks per zero-hallucination.md |

> Source: tad-mapping-blueprint.md Decision 5

---

## Step 4: Anti-Premature-Conclusion Checklist

Before concluding ANY research task (except quick factual), apply the **10 Anti-Premature-Conclusion Rules** from [research-protocol.md](references/research-protocol.md) and the **Completeness Checklist** from the same file.

If any item is unchecked, **continue working instead of concluding**.

### Anti-Skip / Anti-Rationalization Table

The agent WILL be tempted to stop early. Each rationalization below is a known failure mode; the counter cites the existing protocol that forbids it. Do NOT proceed past a row whose left column matches your current thought.

| Rationalization (the excuse) | Counter (the rule it violates) |
|------------------------------|--------------------------------|
| "The first 3 papers agree, I can stop." | Premature saturation. research-protocol.md Rule 1 (≥2 databases) + Rule 9 (count tool calls vs the tier floor in Step 1: 20-40 survey / 80+ systematic). 3 concordant papers ≠ exhaustive search. |
| "Tier is Quick factual, so I can skip ScholarEval / the depth floor." | Re-classify, don't downgrade. If the request says "review / survey / systematic / meta-analysis" it is NOT Quick factual — match Step 1 signal keywords honestly. ScholarEval ≥ 0.75 is the Gate 3 Accept bar for any non-trivial tier. |
| "The API returned empty, so the topic must have no literature." | Empty result ≠ no literature. fallback-chains.md 3-strike rule: try the alternative database/query before declaring a source failed. zero-hallucination.md FORBIDS substituting training knowledge for a 0-result search. |
| "The abstract said so, I'll cite it from memory." | zero-hallucination.md 4-point check: every citation detail (title/authors/DOI/count) MUST come from a tool result in THIS session. Reciting from memory = fabrication. |
| "Close enough — I'll write the report now without a Methods section." | research-protocol.md Rule 4: no report without a Methods section (databases queried, result counts, filter criteria). Rule 8: do not end the turn until the report is saved to a file. |
| "Cohen's kappa is fine; I don't need the other agreement metrics." | For systematic-review screening the include class is rare → kappa paradox. literature-search.md §2 requires Gwet's AC1 + raw % agreement alongside kappa when the positive class is rare. |
| "PRISMA is PRISMA — the 27-item checklist covers this scoping review." | Wrong instrument. literature-search.md PRISMA decision rule: scoping review → PRISMA-ScR (20+2 items); only a focused-question systematic review uses PRISMA 2020 (27 items). |

> These rows are referenced from the [Quick Rule Index](#quick-rule-index) below. The full 10 Anti-Premature-Conclusion Rules live in [research-protocol.md](references/research-protocol.md).

---

## Step 5: TAD Integration

| TAD Mechanism | Academic Research Role |
|--------------|----------------------|
| **Gate 3** | Verifies citation integrity (zero-hallucination 4-point check) + ScholarEval score ≥ 0.75 for Accept |
| **Gate 4** | Verifies research completeness per tier (did Blake reach the minimum phase and tool-call threshold?) |
| **Knowledge Assessment** | Runs after Reflexion Cycle for non-trivial tasks — captures reusable research patterns in project-knowledge |
| **Ralph Loop Layer 1** | Checks fallback chain exhaustion (did Blake try alternatives before declaring a source failed?) |

---

## Step 6: Research Memory & Persistence

Research findings persist across sessions via TAD's existing memory stack — no additional infrastructure required.

| Memory Need | TAD Solution | How It Works |
|------------|-------------|-------------|
| Cross-session findings | `.tad/project-knowledge/*.md` | Knowledge Assessment (Gate 3/4) writes reusable discoveries to category files. Blake or Alex reads them on next session via `@import` in CLAUDE.md. |
| Semantic recall across sources | Local Wiki via search.py & canon lookup (NotebookLM as cloud fallback) | Multi-source notebooks (30-50 sources each) enable cross-source synthesis. Query returns grounded answers with source attribution. |
| Per-topic evidence archive | `.tad/evidence/research/{topic}/` | Subdirectories per research topic store raw findings, analysis files, and search logs. Persists across handoffs within an Epic. |
| Self-evaluation patterns | Completion report Knowledge Assessment | Reflexion Cycle (reflexion-cycle.md) captures what worked and what failed. Written to completion report, promoted to project-knowledge if reusable. |
| Research notebook portfolio | Local Wiki (`research/canon/_index.md`) primary; `.tad/research-notebooks/REGISTRY.yaml` secondary | Index of all NotebookLM notebooks with topic, source count, and status. Alex creates and curates; Blake queries during implementation. |

**Integration rules:**
- Findings that apply beyond a single handoff → write to `.tad/project-knowledge/` via Knowledge Assessment
- Findings specific to one research question → keep in `.tad/evidence/research/{topic}/`
- Findings worth cross-source synthesis → prefer Local Wiki canon first; ingest into NotebookLM via `*research-notebook ingest` only as cloud fallback
- Do NOT duplicate: choose one persistence path per finding

---

## Quick Rule Index

> Before concluding, re-read the [Anti-Skip / Anti-Rationalization Table](#anti-skip--anti-rationalization-table) in Step 4 — it maps each "stop early" excuse to the rule that forbids it.

### Protocol References (Phase 2)

| Reference | What It Covers | When to Read |
|-----------|---------------|-------------|
| [research-protocol.md](references/research-protocol.md) | 6 mandatory phases, depth enforcement, mandatory search protocol | Every non-trivial research task |
| [zero-hallucination.md](references/zero-hallucination.md) | Citation integrity, 4-point self-check, empty-result handling | Every task — this is absolute |
| [scholar-eval.md](references/scholar-eval.md) | 8-dimension weighted quality rubric (0-1 scale) | When evaluating research quality |
| [reflexion-cycle.md](references/reflexion-cycle.md) | 5-dimension post-task self-evaluation | After completing a research task |
| [fallback-chains.md](references/fallback-chains.md) | Source failure recovery, 3-strike rule, fallback tables | When a search/API fails |

### Cluster References (Phase 3) — Domain-Specific Judgment Rules

| Reference | What It Covers | When to Read |
|-----------|---------------|-------------|
| [literature-search.md](references/literature-search.md) | Multi-database search, PRISMA pipeline, citation networks, bibliography management | Literature reviews, systematic reviews |
| [database-apis-general.md](references/database-apis-general.md) | Semantic Scholar, OpenAlex, PubMed, arXiv, World Bank, CrossRef API templates | Any database query task |
| [database-apis-life-sciences.md](references/database-apis-life-sciences.md) | UniProt, ChEMBL, NCBI, PDB, ClinicalTrials, KEGG, STRING API templates | Life science research |
| [statistics.md](references/statistics.md) | Test selection, meta-analysis (DerSimonian-Laird, I²), effect sizes, power analysis, APA reporting | Any quantitative analysis |
| [writing.md](references/writing.md) | IMRaD structure, grant writing (NIH/NSF), LaTeX, citation styles, journal page limits | Writing research outputs |
| [visualization.md](references/visualization.md) | Publication figures (300+ DPI), journal palettes, chart selection, statistical plots | Creating figures |
| [domain-biomedical.md](references/domain-biomedical.md) | Bioinformatics (FDR<0.05), clinical trials, CONSORT, drug discovery, protein analysis | Biomedical research |
| [domain-physical.md](references/domain-physical.md) | Molecular dynamics, materials screening, signal processing, computational chemistry | Physical/computational science |
| [domain-social.md](references/domain-social.md) | Econometrics (DiD, RDD, IV), survey methods, psychometrics, education research | Social science research |
| [experiment-design.md](references/experiment-design.md) | RCT design, sample size, GRADE, Cochrane RoB, reproducibility, IRB, peer review | Experiment planning |
| [multimodal-research.md](references/multimodal-research.md) | Image analysis protocol, observation-before-interpretation, measurement fallbacks, image citation, cross-image comparison | Image-based research tasks |
| [pattern-extraction.md](references/pattern-extraction.md) | Motif identification, line abstraction (3 levels), cross-cultural feature matrix, ornamental vocabulary (guilloche, arabesque, etc.) | Visual pattern / ornament studies |
| [quantitative-analysis.md](references/quantitative-analysis.md) | image-analysis.py decision matrix, similarity/frequency thresholds, output interpretation, qualitative-quantitative integration | When using CV tools for measurement |

---

## Available Tools

### `scripts/academic-search.sh` — Database Query Helper

Reusable bash script for querying academic databases with rate limiting and structured output.

```bash
academic-search.sh <database> "<query>" [--limit N]
```

Supported databases: `semantic-scholar`, `openalex`, `pubmed`, `arxiv`, `europeana` (requires EUROPEANA_API_KEY), `usda-food` (DEMO_KEY or USDA_API_KEY).

### `scripts/image-analysis.py` — Quantitative Image Analysis

Python toolkit for CV-based image measurement. Requires setup: `bash scripts/setup-cv.sh`

```bash
~/.academic-research-cv-venv/bin/python3 scripts/image-analysis.py edges input.jpg --output edges.svg
~/.academic-research-cv-venv/bin/python3 scripts/image-analysis.py colors input.jpg --output colors.json
~/.academic-research-cv-venv/bin/python3 scripts/image-analysis.py match img1.jpg img2.jpg --output result.json
~/.academic-research-cv-venv/bin/python3 scripts/image-analysis.py frequency input.jpg --output freq.json
~/.academic-research-cv-venv/bin/python3 scripts/image-analysis.py features input.jpg --output features.json
```

See [quantitative-analysis.md](references/quantitative-analysis.md) for decision matrix and output interpretation.

Use this script during research Phase 1 (Discovery) and Phase 4 (Database Cross-Verification) instead of writing raw curl commands.

---

## Notes

- **Skill evolution**: This pack improves via TAD's existing *optimize → proposal → human approval → handoff cycle (not runtime generation). See tad-mapping-blueprint.md Decision 4
- **Memory**: Uses TAD's file-based project-knowledge + optional NotebookLM notebooks. See Step 6 for the full memory integration mapping
- **Source coverage**: 86 unique ScienceClaw skills cited across 15 reference files (consolidated from 150 P1+P2 skills)