stanford-research
Skill0 starsChanged 4 months agoMITView on GitHub
Analyze academic papers as rigorous literature synthesis across claims, contradictions, citation chains, gaps, methods, assumptions, knowledge maps, and practical meaning. Use when user says "stanford research", requests literature synthesis, paper intake, contradiction finder, gap scan, methodology audit, assumption audit, knowledge map, or plain-language "so what" summary.
In this repository16 other files it gives its agents.
- AGENTS.mdAGENTS.md
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The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 4 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 11
Use supplied papers only unless user authorizes outside research.
- Distinctive: line 32
Keep only mutually incompatible claims about same issue.
- Very specific: line 65
Use calibrated language. Proves requires design that supports causal certainty.
- Distinctive: line 89
Use plain language. Keep uncertainty.
- Distinctive: line 100
Every substantive claim traces to paper.
- Distinctive: line 110
Use direct simple sentences.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Synthesize paper set into evidence, disputes, methods, gaps, assumptions, and meaning. Trace every claim.
Scope
Use supplied papers only unless user authorizes outside research. Named subtask runs only that module. stanford research or full protocol runs all modules. Do not use for narrative essay drafting or single-paper copyedit.
Inputs
- Full paper text or readable files.
- Research question and intended audience.
- Citation style and output depth.
- Permission boundary for outside sources.
Authors own claims. User owns paper set and research question. Mark unavailable text, missing metadata, inference, and unresolved ambiguity.
Workflow
Step 1: Intake
For each paper capture author, year, research question, method, data, core claim, and stated limits. Write thesis in 20 words or fewer; label inference when abstract/conclusion lacks explicit thesis.
Cluster papers by shared question, framework, method, or assumption. Name basis. Flag candidate contradictions.
Step 2: Test Contradictions
Keep only mutually incompatible claims about same issue. Exclude differences caused only by scope, emphasis, wording, population, or outcome definition.
For each contradiction state positions, papers, evidence, and root cause: method, dataset, period, definition, population, or unresolved cause.
Step 3: Trace Concepts
For recurring concepts, map origin within supplied set, challenge, refinement, and current status: settled in set, contested, evolving, or unsupported. Do not claim historical origin beyond available corpus.
Step 4: Find Gaps
Separate:
- Author-acknowledged gap.
- Gap implied by method or data.
- Analyst-proposed gap.
For each, name closest paper, shortfall, why gap matters, and method/data needed. Rank by stated criterion: theoretical impact, practical impact, or feasibility.
Step 5: Audit Methods
Compare design, data source, sample, measures, identification strategy, controls, reproducibility, and author-stated limits. Use method labels that fit papers; do not force preset taxonomy.
Name strongest and weakest evidence for specific claim, not globally strongest or weakest paper. Explain criterion.
Step 6: Synthesize
Organize by claim, not paper:
- Consensus supported by at least two papers when available.
- Active debates and reason for disagreement.
- Strongest evidence and why it is stronger.
- Open question whose answer most changes field.
Use calibrated language. Proves requires design that supports causal certainty. Distinguish absence of evidence from evidence of absence.
Step 7: Audit Assumptions
Find consequential assumptions shared by multiple papers but not tested or justified. For each, state relying papers, risk if false, and affected conclusions. Rank by consequence, not novelty.
Step 8: Build Knowledge Map
Return outline:
- Central claim or competing centers.
- Three to five supporting pillars with papers.
- Two or three contested zones when present.
- One or two frontier questions.
- Three-paper newcomer path selected for foundation and sequence, not citation count.
Step 9: Explain Meaning
For non-expert summary, answer:
- Best-supported finding.
- Largest unresolved question.
- Why it matters in practice or theory.
Use plain language. Keep uncertainty. No jargon or unsupported certainty.
Fallbacks
- Missing full text: limit claims to available sections and say so.
- Small set: report all supported contradictions/gaps; do not pad counts.
- Incomparable papers: split by population, method, or outcome before synthesis.
- Outside research not authorized: stop at supplied corpus.
Verify
- Every substantive claim traces to paper.
- Direct quote and paraphrase distinguished.
- Contradictions compare same construct and scope.
- Gaps labeled by source type.
- Method judgments cite criteria.
- Certainty matches design and evidence.
- Missing evidence and corpus limits explicit.
Writing
Use direct simple sentences. Skip rhetorical flourishes. Avoid X-not-Y contrasts, self-answering rhetorical questions, em dashes, alliterative three-part phrases, vague inspirational pivots, unsourced claims, and unverified quotes.
Output
Return requested module or full protocol. Use compact comparison tables only where they improve cross-paper mapping. Include citations and corpus-limit note.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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- It worked
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

