research-planning
Skill3 starsChanged 8 months agoMITView on GitHub
Use when starting or reframing a computer science research project and you need to turn a vague idea into a scoped plan with research questions, milestones, risks, and next actions.
7 other projects use a version of this.
Adopted by
Most recently taken up by
- WilliamEbong/CourseForgetheir own version, first seen Nov 8, 2026
- mattmireles/gemma-tuner-multimodaltheir own version, first seen Nov 1, 2026
- willlee1995/skillstheir own version, first seen Oct 13, 2026
- stritar/skillstheir own version, first seen Sep 11, 2026
- sivaguru-2113/Agent-personatheir own version, first seen Aug 18, 2026
- dongzhigang13305312738-art/paper-skillstheir own version, first seen Jul 21, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 7
- mattmireles/gemma-tuner-multimodal★ 1.5ksame name
- lingzhi227/agent-research-skills★ 350same name
- dongzhigang13305312738-art/paper-skills★ 1same name
- sivaguru-2113/Agent-persona★ 1same name
- willlee1995/skills★ 1same name
- stritar/skills★ 0same name
- WilliamEbong/CourseForge★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository43 other files it gives its agents.
- agent-codingSkill
- benchmark-designSkill
- citation-managementSkill
- code-reproductionSkill
- code-to-paperSkill
- daskSkill
- experiment-trackingSkill
- exploratory-data-analysisSkill
- get-available-resourcesSkill
- github-release-prepSkill
- latex-postersSkill
- literature-reviewSkill
- markdown-mermaid-writingSkill
- markitdownSkill
- matplotlibSkill
- modalSkill
- networkxSkill
- paper-to-codeSkill
- peer-reviewSkill
- plotlySkill
- polarsSkill
- pytorch-lightningSkill
- pyzoteroSkill
- repo-cleanupSkill
- reviewer-responseSkill
- scholar-evaluationSkill
- scientific-critical-thinkingSkill
- scientific-schematicsSkill
- scientific-slidesSkill
- scientific-visualizationSkill
- scientific-writingSkill
- scikit-learnSkill
- seabornSkill
- shapSkill
- stable-baselines3Skill
- statistical-analysisSkill
- statsmodelsSkill
- sympySkill
- torch-geometricSkill
- transformersSkill
- umap-learnSkill
- vaexSkill
- venue-templatesSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 6 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 42
avoid vague tasks like "do research" without outputs
- Distinctive: line 43
prefer falsifiable or testable questions when possible
- Distinctive: line 45
keep the first milestone small enough to execute immediately
“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Purpose
Turn an idea, problem statement, or paper goal into an executable CS research plan.
When To Use
- starting a new paper, thesis thread, or research prototype
- comparing several candidate directions before implementation
- decomposing a broad topic into concrete work packages
- needing a milestone plan for literature, coding, experiments, and writing
Inputs
- rough idea, question, or target venue
- constraints on time, compute, data, or collaborators
- relevant papers, repos, datasets, or notes if available
Outputs
- scoped research objective
- concrete research questions or hypotheses
- task breakdown by workstream
- milestone sequence and decision points
- risk list with fallback plans
- immediate next actions
Workflow
- Clarify the target artifact: paper, benchmark, reproduction, prototype, or thesis chapter.
- Fix hard constraints before expanding scope.
- Split work into literature, implementation, experiments, and writing tracks.
- Convert the plan into milestones with visible acceptance criteria.
- Surface risks, dependencies, and the minimum viable first step.
Constraints
- avoid vague tasks like "do research" without outputs
- prefer falsifiable or testable questions when possible
- distinguish required work from optional stretch work
- keep the first milestone small enough to execute immediately
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.