snowball

Research

Citation-chain-driven literature survey starting from seed papers. Traces research lineage in both forward (who cited this) and backward (what this cited) directions until saturation. High deep-read ratio (67%). Use when the user already has key papers and wants to find everything connected to them — ancestors, descendants, and branch points.

QUICK START

How to use this skill

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Prompt to paste

I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/yogsoth-ai/de-anthropocentric-research-engine/blob/HEAD/skills/snowball/SKILL.md

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Snowball

Purpose: Seed-first, forward/backward tracing — start from known seed papers and trace the research lineage in both directions.

When to use: User already has key papers and wants to find everything connected to them — what they built on, what built on them.

Budget

Base SOP	Target	±10% Range
web-search	20 results	18–22
web-research	3 pages	2–4
paper-overview	30 papers	27–33
paper-search	30 papers	27–33
paper-research	20 papers	18–22

State Ledger

Print this table before each major iteration decision:

| SOP            | Target | Current | % Complete |
|----------------|--------|---------|------------|
| web-search     | 20     | ???     | ???%       |
| web-research   | 3      | ???     | ???%       |
| paper-overview | 30     | ???     | ???%       |
| paper-search   | 30     | ???     | ???%       |
| paper-research | 20     | ???     | ???%       |

Do not exit the strategy until all rows reach ≥90%.

Available Tactics

citation-chaining — forward/backward citation expansion until saturation

Available SOPs

Import (strict protocol execution):

web-search → web-browsing/skills/web-search/SKILL.md
web-research → web-browsing/skills/web-research/SKILL.md
paper-overview → literature-engine/skills/literature-overview/SKILL.md
paper-search → literature-engine/skills/literature-search/SKILL.md
paper-research → literature-engine/skills/literature-research/SKILL.md

Subagent (CC decides when to invoke):

seed-selection — validate and prioritize starting papers
saturation-detection — determine when to stop (diminishing returns)
gap-identification — find what the literature hasn't addressed
survey-synthesis — produce final structured output

Execution Guidance

seed-selection validates and prioritizes the starting papers
citation-chaining is the primary operation — iterate until saturation
saturation-detection determines when to stop (diminishing returns)
Minimal web-search (only for context that papers don't provide)
High paper-research ratio (20/30 = 67% deep-read rate) — trace papers deserve thorough reading
Build a clear lineage: who influenced whom, how ideas evolved

Output Format

Research Lineage Map containing:

Seed papers → ancestors (backward trace)
Seed papers → descendants (forward trace)
Evolution of ideas across generations
Key branch points where the field diverged
Current frontier (most recent descendants)
Lineage visualization (text-based DAG)

Available Tactics

Optional, no fixed order; the final leaf is always a sop.

Tactic	When to use
citation-chaining	Forward and backward citation tracing tactic — expand paper coverage by tracing citation networks in both directions from seed/key papers. Alternates forward (who cited this) and backward (what this cited) passes until saturation.

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOP	When to use
knowledge-acquisition-gap-identification	Identify what the literature has NOT addressed — missing methods, untested combinations, unexplored applications, contradictions without resolution. Used by all strategies.
knowledge-acquisition-paper-overview	Abstract-level paper scanning for broad coverage. Import of literature-engine/literature-overview skill. Abstract-level only — no methodology conclusions from abstracts.
knowledge-acquisition-paper-research	Full-depth paper reading with raw text extraction. Import of literature-engine/literature-research skill. Must read fullText (true) — equations, hyperparameters, specific claims extracted.
knowledge-acquisition-paper-search	AI-summarized paper reading for intermediate depth. Import of literature-engine/literature-search skill. Must call get_paper_content for every analyzed paper.
knowledge-acquisition-saturation-detection	Determine when additional searching yields diminishing returns. Analyzes the latest expansion batch against existing corpus to judge continue/near-saturation/saturated. Used by snowball and systematic-survey.
knowledge-acquisition-web-research	Full-page web reading for non-academic perspectives — blogs, tech reports, product pages, industry analysis. Import of web-browsing/web-research skill. Must fetch full page via apify for every analyzed page.
knowledge-acquisition-web-search	Quick web scanning for landscape understanding. Import of web-browsing/web-search skill. Snippets only — no conclusions from snippets alone.
seed-selection	Validate and prioritize starting papers for snowball surveys. Evaluates which seeds will yield the richest citation traces based on citation count, recency, and network position.
survey-synthesis	Final synthesis step — weave all gathered evidence (reading notes, extracted data, categorizations) into a coherent structured output appropriate to the strategy type. Used by all 5 strategies as the final step.