academic-slides
Use this skill for creating or refining an academic slide deck and the talk built around it:…
Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary section refinement → final assembly. Produces survey-grade output with
$ npx -y skills add evoscientist/evoskills --skill research-survey --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/research-surveyContext preview
The summary Claude sees to decide when to auto-load this skill.
Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary section refinement → final assembly. Produces survey-grade output with
name: research-survey description: "Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary section refinement → final assembly. Produces survey-grade output with taxonomy-based method analysis, LaTeX formalizations, comparative tables, and dense citations. Use when: user wants a literature review, research survey, field overview, or systematic synthesis of multiple papers. Do NOT use for finding/searching papers (use paper-navigator), generating research ideas (use research-ideation), or writing a paper's Related Work section (use paper-writing)." allowed-tools: "write_file edit_file read_file think_tool" metadata: author: EvoScientist version: '1.0.0' tags: [core, research, literature, survey, synthesis]
Generates high-quality, survey-grade literature reviews from papers collected by `paper-navigator`.
paper-navigator (collect 30-120 papers)
↓
Stage 1: Generate Outline (query-type adaptive structure)
↓
Stage 2: Draft Survey (outline + top-30 papers)
↓
Stage 3: Expand Sections (draft + all papers, section-by-section)
↓
Stage 4: Generate Section Summaries
↓
Stage 5: Refine Summary Sections (Abstract/Intro/Conclusion)
↓
Stage 6: Assemble + ReferencesThis skill requires papers as input. If the user hasn't provided papers, **first invoke `paper-navigator`** (Workflow 1, target 30-120 papers) to collect them.
**CRITICAL: All paper discovery MUST use the `paper-navigator` skill and its scripts (scholar_search, citation_traverse, arxiv_monitor, recommend, etc.). Using WebSearch, WebFetch, or any generic web search tool for finding papers is PROHIBITED.** Generic web search cannot access Semantic Scholar, citation graphs, or academic recommendation systems. Only `paper-navigator` provides the academic search infrastructure needed for survey-quality literature collection.
---
**This is a two-phase process.** Different fields have different survey conventions — a clinical systematic review looks nothing like a CS methods survey. First generate a domain-appropriate template, then create the detailed outline.
Before outlining, identify the field and adapt the structure:
1. **Identify the field** from the user's goal and collected papers 2. **Select section names and organization logic** using the field-specific conventions in `assets/survey-template.md` (e.g., medicine organizes by intervention type and follows PRISMA; chemistry organizes by reaction class; social sciences organize by theoretical perspective) 3. **Add field-specific sections** (e.g., Risk of Bias Assessment for medicine, Structure-Property Relationships for materials, Ethical Considerations for human-subjects research) 4. **Determine comparison table dimensions** appropriate to the field
With the domain-specific template as the framework, generate the outline:
| Type | Example | Structure | |------|---------|-----------| | **A: Single-topic deep dive** | "Catalyst design for electrochemical CO2 reduction" | Intro → Problem Definition → **Methods (by mechanism/approach)** → Evaluation → Challenges → Conclusion | | **B: Multi-topic parallel** | "Drug resistance mechanisms and therapeutic strategies in cancer immunotherapy" | Intro → **Topic 1 (definition + methods)** → **Topic 2 (definition + methods)** → Evaluation → Challenges → Conclusion | | **C: Pipeline/stage-based** | "From sample preparation to data analysis in single-cell RNA sequencing" | Chapters organized by workflow stages |
The outline is NOT a simple heading list — it's a **blueprint with meta-instructions** for each section. For each `## Section`:
See `references/survey-methodology.md` for full outline generation rules and `assets/survey-template.md` for field-specific conventions.
---
Generate a complete draft from the outline using the **top-30 most relevant papers**.
---
Expand each non-summary section using **all collected papers** (30-120). This is where survey-grade depth is achieved.
| Section Type | Target Length | Focus | |---|---|---| | **Methods** | 6000+ words per paradigm chapter | Technical narratives, mechanism analysis, comparison tables | | **Evaluation** | 3500+ words | Benchmark taxonomy, metric analysis, SOTA summary | | **Challenges** | 3000+ words | Problem definition + evidence + opportunity per challenge | | **Applications** | 3000+ words | Real-world use cases with specific achievements | | **Problem Definition** | 2000+ words | LaTeX formalization, constraints, assumptions | | **Other*
The official skill repository for EvoScientist. Each skill is an installable knowledge pack that extends EvoScientist with domain-specific expertise.
Use this skill for creating or refining an academic slide deck and the talk built around it:…
Manages persistent research memory across ideation and experimentation cycles. Maintains two…
Use this skill whenever the user submits a non-trivial mathematical claim that needs a…
Use this skill when the user wants to debug, diagnose, or systematically iterate on an…
Iterative code refinement through plan → code → evaluate → refine cycles. Runs lint checks…
Guides structured 4-stage experiment execution with attempt budgets and gate conditions:…