Skill: exhaustive long-context coverage

[Case 2]

• Initial Environment: A large collection of short scholarly biography documents, each describing the career of a single award winner, including their primary research area and nationality.
• Real Question: What is the distribution of all Turing Award winners by their fields of study by 2023?
• Real Trajectory: 1. Scan the entire document set to build a master list of all identified Turing Award winners. 2. For each identified person, locate and extract the specific field of study mentioned. 3. Aggregate the individual field assignments. 4. Synthesize the final comprehensive distribution logic.
• Real Answer: As of 2023, the Turing Award winners are distributed across various fields: Artificial Intelligence (X winners), Cryptography (Y winners), Database Systems (Z winners)... [Full exhaustive list provided].
• Why this demonstrates the capability: The answer requires exhaustive entity recall across dozens of documents. Failure to read even one document or misattributing a field to the wrong winner degrades the accuracy of the statistical distribution.

[Case 3]

• Initial Environment: A RAG context containing a massive 75-page Advanced Persistent Threat (APT) report detailing an operating sequence. The tool used for execution and the resulting file suffix are separated by thirty pages of irrelevant log data.
• Real Question: What is the specific command-line argument used for data compression in the observed exfiltration sequence, and what file extension does the resulting archive use?
• Real Trajectory: 1. Scan the 75-page report for data collection parameters. 2. Extract the '-mx9' command argument on page 14. 3. Skip extensive background narratives. 4. Locate the discontinuous token span on page 19 describing the '.tmp.enc' suffix. 5. Merge the fragmented pieces into a localized whole.
• Real Answer: The command-line argument used for compression is '-mx9' and the resulting exfiltration files use the '.tmp.enc' extension.
• Why this demonstrates the capability: The relevant evidence is completely discontinuous. The specific facts are separated by dozens of irrelevant paragraphs, requiring sub-document tracking and multi-span bridging without summarizing the useless middle noise.

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:

1. Phase 1: Environment Exploration Read the exploration guidelines to discover raw knowledge seeds: references/EXPLORATION.md

2. Phase 2: Trajectory Selection Once Phase 1 is complete, read the selection criteria to evaluate the trajectory: references/SELECTION.md

3. Phase 3: Data Synthesis Once a trajectory passes Phase 2, read the synthesis instructions to generate the final data: references/SYNTHESIS.md