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zackz2025

Academic Deep Search

by Zack · GitHub ↗ · v2.1.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install academic-deep-search
Description
Search academic literature and return structured, source-grounded results for questions about methods, markers, findings, or representative figures. Use this...
README (SKILL.md)

Academic Deep Search

Use this skill for requests such as:

  • "What markers do studies on topic X usually measure?"
  • "What do results sections in this field usually report?"
  • "Show me a typical figure for this disease model or pathway."
  • "What experimental methods are commonly used in this literature?"

The goal is not just to find papers. The goal is to read enough of the right papers to give the user a structured, directly useful answer.

Two Output Modes

Choose the mode that best matches the user request.

Body Mode

Use when the user asks about:

  • molecules or markers commonly measured
  • methods commonly used
  • what findings usually appear in Results sections

Organize the answer by experiment type or finding category, not by paper.

Figure Mode

Use when the user asks for:

  • a typical figure in a topic
  • how findings are visually presented
  • figure captions or representative panels

Organize the answer by figure, with source attribution and caption context.

Workflow

1. Clarify The Research Question

Identify:

  • the topic or disease area
  • whether the user wants methods, markers, findings, or figures
  • whether the user named a specific journal, database, or URL
  • whether the topic is biomedical or from another field

If the topic is biomedical, translate the idea into standard English search terms and prefer controlled vocabulary when possible.

2. Respect Source Scope First

If the user specifies a source, that scope is binding.

Examples:

  • if the user says PubMed, do not mix in Google Scholar
  • if the user names specific journals, search only those journals
  • if the user gives a URL, read that source directly before searching elsewhere

Do not silently broaden the source list.

3. Build Search Terms Carefully

Use English search terms for database queries, even if the conversation is in Chinese.

For biomedical topics:

  • prefer MeSH or other standardized vocabulary when available
  • generate a few close variants or synonyms
  • keep journal names exact when filtering by journal

Detailed query construction tips are in references/query-guide.md.

4. Search For Candidate Papers

Prefer the best database for the topic:

  • biomedical: PubMed or PMC first
  • quantitative or engineering topics: field-appropriate databases
  • broad discovery: web search only when a better native source is unavailable

Aim to identify a small set of relevant papers with accessible full text. A few well-read papers are better than many shallow hits.

5. Verify Source Membership Before Citing

Before you cite a paper as belonging to a target journal or source, verify it.

Check:

  • journal field on the abstract page or database result
  • exact source metadata in the database
  • whether the paper truly matches the user-specified scope

Do not attribute a paper to a journal or database unless you confirmed it.

6. Read Full Text Strategically

Abstract-only answers are usually not enough.

Read:

  • Methods, Results, and Discussion for Body Mode
  • figure captions plus the relevant Results text for Figure Mode

If full text is not available, say that clearly and lower confidence.

7. Select And Synthesize

Choose 2 to 5 papers that are:

  • relevant to the question
  • compliant with the requested source scope
  • diverse enough to avoid overgeneralizing from one paper
  • rich enough in methods, results, or figures to support the answer

Then synthesize across papers instead of writing a paper-by-paper summary unless the user asked for that.

Output Rules

  • Answer directly in chat unless the user asks for a file.
  • Use inline citations such as PMID, PMCID, DOI, or direct links.
  • Be explicit about what was actually read.
  • If evidence is limited, say so plainly.

Use references/query-guide.md for output templates.

Non-Negotiable Rules

  • User-specified source scope overrides your defaults.
  • Do not answer methods or marker questions from abstracts alone if full text is available.
  • Do not fabricate source membership or figure details.
  • Prefer PubMed and PMC for biomedical literature.
  • Translate search intent into English for querying, but answer in the user's language when appropriate.

If Results Are Sparse

When little is found:

  • broaden or narrow terms thoughtfully
  • try synonyms or controlled vocabulary
  • explain what was searched and why the yield was limited
  • suggest the next best search strategy
Usage Guidance
This skill appears coherent and low-risk because it is purely procedural text (no code, no installs, no credentials). Before installing: confirm your agent runtime has safe network policies (it will access PubMed/PMC or other web databases), avoid giving the skill any private/unpublished URLs or credentials unless you trust the target, and be aware that paywalled articles may be inaccessible — the skill will lower confidence if full text is unavailable. If you require stricter scope control, ask that the skill only use explicit databases (e.g., PubMed only) or require the user to provide exact URLs for paywalled content.
Capability Analysis
Type: OpenClaw Skill Name: academic-deep-search Version: 2.1.0 The skill is a legitimate tool designed for academic literature search and synthesis, specifically targeting biomedical databases like PubMed and PMC. The instructions in SKILL.md and references/query-guide.md focus on structured research workflows, source verification, and data synthesis without any evidence of malicious intent, data exfiltration, or unauthorized command execution.
Capability Assessment
Purpose & Capability
Name and description match the SKILL.md instructions: guidance on building searches, preferring PubMed/PMC for biomedical topics, selecting and reading papers, and synthesizing results. No unrelated capabilities or required resources are requested.
Instruction Scope
Runtime instructions focus on query construction, source scoping, verifying journal membership, reading Methods/Results/Figures, and synthesis. The instructions do not direct the agent to read unrelated local files, environment variables, or to transmit data to unknown endpoints.
Install Mechanism
No install spec and no code files — instruction-only skill. This minimizes disk-write and execution risk.
Credentials
The skill requests no environment variables, credentials, or config paths. The only implied requirement is network access to public databases (e.g., PubMed/PMC), which is proportionate to the stated purpose.
Persistence & Privilege
always:false (not force-included), user-invocable, and model invocation enabled (the platform default). No requests to modify other skills or system-wide settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install academic-deep-search
  3. After installation, invoke the skill by name or use /academic-deep-search
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.1.0
Restructured the skill for cleaner source-aware literature search, added query guidance, and improved output rules.
v2.0.2
v2.0.2: SKILL.md only, clean local state
v2.0.1
v2.0.1: remove README and .git, SKILL.md only, clean git history
v2.0.0
v2: universal, MeSH-compliant, user-scope-first, no domain-specific examples, SKILL.md only
v1.0.0
Initial release: English-only academic literature search skill with Body Mode (results by experiment type) and Figure Mode (figures with captions). Supports all academic fields; biomedical searches prioritize PubMed/PMC.
Metadata
Slug academic-deep-search
Version 2.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 5
Frequently Asked Questions

What is Academic Deep Search?

Search academic literature and return structured, source-grounded results for questions about methods, markers, findings, or representative figures. Use this... It is an AI Agent Skill for Claude Code / OpenClaw, with 198 downloads so far.

How do I install Academic Deep Search?

Run "/install academic-deep-search" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Academic Deep Search free?

Yes, Academic Deep Search is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Academic Deep Search support?

Academic Deep Search is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Academic Deep Search?

It is built and maintained by Zack (@zackz2025); the current version is v2.1.0.

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