dingxingdi Skill: full-text literature synthesis
1. Capability Definition & Real Case
- Professional Definition: The ability to answer scientific questions by retrieving full-text papers, extracting evidence from relevant sections beyond superficial summaries, and synthesizing a cited answer with calibrated uncertainty when the evidence remains insufficient. The capability combines literature retrieval, section-level evidence gathering, and answer calibration.
- Dimension Hierarchy: Specialized Knowledge Navigation->Corpus-Specific Retrieval & Reasoning->full-text literature synthesis
Real Case
[Case 1]
- Initial Environment: A bounded corpus of recent biomedical full-text papers published after common model cutoff dates. The decisive evidence is inside a paper’s body rather than safely recoverable from an abstract-only summary.
- Real Question: Has anyone performed a base editing screen against splice sites in CD33 before?
- Real Answer: Yes
- Why this demonstrates the capability: The question targets a recent scientific finding and is intentionally difficult to answer from latent memory alone. The agent must retrieve the right paper, inspect relevant full-text sections, and synthesize a bounded answer. This is the core retrieval-and-synthesis pattern for literature RAG.
[Case 2]
- Initial Environment: A bounded recent-paper corpus in neuroscience. The relevant evidence compares laminar patterns between two neuron groups and must be extracted from the paper content.
- Real Question: How diffuse are the laminar patterns of the axonal terminations of lower Layer 5/Layer 6 intratelencephalic neurons compared to Layer 2-4 intratelencephalic neurons in mouse cortex?
- Real Answer: More diffuse
- Why this demonstrates the capability: This case tests whether the agent can retrieve specialized literature and read enough of the paper to answer a fine-grained comparative question. The answer is compact, but the supporting evidence is not a generic factoid. The capability is therefore full-text scientific synthesis rather than keyword lookup.
[Case 3]
- Initial Environment: A bounded recent-paper corpus in immunology or molecular biology. The question asks which listed glycoRNA does not display a specified increase under stimulation conditions.
- Real Question: Which of these glycoRNAs does NOT show an increase in M0 macrophages upon stimulation with LPS: U1, U35a, Y5 or U8?
- Real Answer: U8
- Why this demonstrates the capability: The agent must retrieve the correct paper, inspect the relevant result, and resist plausible distractor options. The question is closed-form, but the underlying skill is still full-text evidence discovery and careful answer selection. This makes it a strong calibration case for literature-grounded RAG.
Pipeline Execution Instructions
To synthesize data for this capability, you must strictly follow a 3-phase pipeline. Do not hallucinate steps. Read the corresponding reference file for each phase sequentially:
Phase 1: Environment Exploration Read the exploration guidelines to discover raw knowledge seeds:
references/EXPLORATION.mdPhase 2: Trajectory Selection Once Phase 1 is complete, read the selection criteria to evaluate the trajectory:
references/SELECTION.mdPhase 3: Data Synthesis Once a trajectory passes Phase 2, read the synthesis instructions to generate the final data:
references/SYNTHESIS.md