skills/method-section-explainer/SKILL.md
Plan and draft ML/AI method sections. Use for notation flow, module ordering, algorithm boxes, overview figures, design rationale, and appendix boundaries.
npx skillsauth add a-green-hand-jack/ml-research-skills method-section-explainerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Explain methods so reviewers can understand what is new, how it works, and why each design choice exists. This skill is for writing and structuring the method section, not inventing the algorithm.
Use this skill for:
Do not use this skill for designing a new algorithm. Use algorithm-design-planner for method design. Use paper-writing-assistant for broad prose. Use paper-writing-memory-manager to record notation, method terminology, overview-figure dependencies, and stale result/caption locations. Use figure-results-review for figure quality. Use paper-draft-consistency-editor after the section exists.
<installed-skill-dir>/
├── SKILL.md
├── references/
│ ├── method-structure-patterns.md
│ └── notation-and-rationale.md
└── templates/
└── method-explanation-plan.md
references/method-structure-patterns.md.references/notation-and-rationale.md when writing notation, equations, algorithm boxes, design rationale, or appendix boundaries.templates/method-explanation-plan.md when creating paper/.agent/method-explanation-plan.md.paper/.agent/writing-contract.md, paper/.agent/writing-memory/, algorithm specs, design docs, method notes, sections/method*.tex, sections/approach*.tex, figures/*.tex, and appendix files when present.Extract:
## Method Explanation Snapshot
- Paper archetype:
- Method type:
- Target venue:
- Main method claim:
- Proposed object:
- Inputs/outputs:
- Key components:
- Training objective:
- Inference procedure:
- Overview figure:
- Algorithm box:
- Required notation:
- Appendix material:
- Reader confusion risks:
If the method itself is underspecified, route to algorithm-design-planner before drafting final prose.
Read references/method-structure-patterns.md and choose one pattern:
The pattern determines subsection order and what belongs in the main text.
Create or update:
paper/.agent/method-explanation-plan.md
If there is no paper/ directory and the current directory is the paper repo, save to:
.agent/method-explanation-plan.md
Use templates/method-explanation-plan.md.
For each subsection, record:
For each subsection:
When revising LaTeX, preserve labels, refs, citations, macros, and math unless they are part of the requested edit.
Keep in main text:
Move or defer to appendix:
Before finalizing:
paper-writing-memory-manager — record locked notation decisions, module/component naming, algorithm box present/absent, overview figure dependency, and which downstream sections (results, captions, appendix) depend on method terminologytesting
Bootstrap project-local ml-research-skills. Use from global installs when creating a new ML research project, enabling this collection in an existing ML research repo, or deciding whether to install the full bundle locally. Route to project-init for new projects; do not handle paper or experiment work directly.
development
Route project operations tasks — git, memory, bootstrap, remote, workspace, code review, timeline, ops — to the correct skill. Use when the task involves commits, pushes, worktrees, project memory, enabling project-local skills, SSH/server coordination, sidecar runners, or audits. Do not solve the ops task directly.
testing
Route ML/AI paper writing tasks to the correct skill — contract planning, prose drafting, section writing, consistency editing, review simulation, rebuttal, submission, or citation work. Use when the task involves writing, revising, reviewing, or submitting a paper instead of guessing between paper-writing-assistant, paper-writing-contract-planner, paper-reviewer-simulator, auto-paper-improvement-loop, or citation skills. Do not draft prose directly.
data-ai
Project-local router for ML research skill selection. Use inside an initialized ML research project, or while maintaining this skill repo, when the user describes an ML research/paper/experiment/discovery/ops/release workflow and may not know the skill; route to a domain router or high-signal leaf. Do not use for generic non-ML projects.