How do I install the Academic Alpha Scanner skill?

Run npx skillmds@latest add knuckles-team/academic-alpha-scanner in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Academic Alpha Scanner safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Academic Alpha Scanner?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Academic Alpha Scanner free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Academic Alpha Scanner?

Knuckles-Team (@knuckles-team) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Academic Alpha Scanner by knuckles-team

Name: Academic Alpha Scanner
Author: Knuckles-Team

Academic Alpha Scanner

Discover academic market-factor research, audit its evidence, extract comparable hypotheses, obtain the required market data, and backtest the candidates by composing package-owned and universal atomic skills. Use when a quantitative researcher wants an evidence-linked screening report for candidate alpha factors, not live trading or investment advice.

Knuckles-Team 3240ff3 2 files · 2.8 KB Updated Sep 17, 2026

File contents

Academic Alpha Scanner Workflow

Compose the package-owned ScholarX skill and named universal atomic skills. Keep research findings and backtest results clearly separate from investment advice or live-order execution.

Inputs

Provide the research question, markets, asset universe, date range, source filters, candidate-selection criteria, data constraints, and backtest assumptions.

Steps

Step 0: scholarx-operations [skill: scholarx-operations]

Invoke $scholarx-operations with the workflow inputs.

Expected: paper_source_packet

Step 1: citation-auditor [skill: citation-auditor] [depends_on: Step 0]

Invoke $citation-auditor with paper_source_packet.

Expected: evidence_audit

Step 2: factor-hypothesis-extractor [skill: factor-hypothesis-extractor] [depends_on: Step 1]

Invoke $factor-hypothesis-extractor with paper_source_packet, evidence_audit, and the workflow inputs.

Expected: candidate_factor_hypotheses

Step 3: quant-data-ingest [skill: quant-data-ingest] [depends_on: Step 2]

Invoke $quant-data-ingest with candidate_factor_hypotheses and the workflow inputs.

Expected: normalized_market_dataset

Step 4: qlib-backtester [skill: qlib-backtester] [depends_on: Step 3]

Invoke $qlib-backtester with candidate_factor_hypotheses, normalized_market_dataset, and the workflow inputs.

Expected: backtest_report

Output

Return paper_source_packet, evidence_audit, candidate_factor_hypotheses, and backtest_report, including the assumptions and limitations emitted by each skill. Do not place or recommend live trades.

Execution

Run first: Step 0 — $scholarx-operations.
After Step 0: Step 1 — $citation-auditor.
After Step 1: Step 2 — $factor-hypothesis-extractor.
After Step 2: Step 3 — $quant-data-ingest.
After Step 3: Step 4 — $qlib-backtester.

Execution: If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.

---name: academic-alpha-scannerdescription: Discover academic market-factor research, audit its evidence, extract comparable hypotheses, obtain the required market data, and backtest the candidates by composing package-owned and universal atomic skills. Use when a quantitative researcher wants an evidence-linked screening report for candidate alpha factors, not live trading or investment advice.license: MIT---# Academic Alpha Scanner WorkflowCompose the package-owned ScholarX skill and named universal atomic skills. Keepresearch findings and backtest results clearly separate from investment advice orlive-order execution.## InputsProvide the research question, markets, asset universe, date range, source filters,candidate-selection criteria, data constraints, and backtest assumptions.## Steps### Step 0: scholarx-operations [skill: scholarx-operations]Invoke `$scholarx-operations` with the workflow inputs.Expected: `paper_source_packet`### Step 1: citation-auditor [skill: citation-auditor] [depends_on: Step 0]Invoke `$citation-auditor` with `paper_source_packet`.Expected: `evidence_audit`### Step 2: factor-hypothesis-extractor [skill: factor-hypothesis-extractor] [depends_on: Step 1]Invoke `$factor-hypothesis-extractor` with `paper_source_packet`, `evidence_audit`,and the workflow inputs.Expected: `candidate_factor_hypotheses`### Step 3: quant-data-ingest [skill: quant-data-ingest] [depends_on: Step 2]Invoke `$quant-data-ingest` with `candidate_factor_hypotheses` and the workflowinputs.Expected: `normalized_market_dataset`### Step 4: qlib-backtester [skill: qlib-backtester] [depends_on: Step 3]Invoke `$qlib-backtester` with `candidate_factor_hypotheses`,`normalized_market_dataset`, and the workflow inputs.Expected: `backtest_report`## OutputReturn `paper_source_packet`, `evidence_audit`, `candidate_factor_hypotheses`, and`backtest_report`, including the assumptions and limitations emitted by each skill.Do not place or recommend live trades.## Execution- **Run first:** Step 0 — `$scholarx-operations`.- **After Step 0:** Step 1 — `$citation-auditor`.- **After Step 1:** Step 2 — `$factor-hypothesis-extractor`.- **After Step 2:** Step 3 — `$quant-data-ingest`.- **After Step 3:** Step 4 — `$qlib-backtester`.**Execution:** If graph-os is reachable, offload the whole DAG via `graph_orchestrate action=execute_workflow` (or the `kg-delegate` skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet `depends_on` in parallel, then their dependents.

Frequently asked questions