semantic-perturbation-translation

# Skill: semantic-perturbation-translation ## 1. Capability Definition & Real Case * **Professional Definition**: The ability to preserve correct translation behavior under higher-level prompt alterations that keep the task semantics intact but introduce role framing, extra explanatory wording, or semantically equivalent reformulations that are farther from the original prompt surface. * **Dimension Hierarchy**: Robustness to Imperfect or Misleading Instructions->Prompt Perturbation Robustness->semantic-perturbation-translation ### Real Case **[Case 1]** * **Initial Environment**: A translation agent receives an English marketing sentence, a target-language constraint, and a role-framed instruction. The source sentence is short and non-technical so the challenge lies in semantic prompt variation rather than source complexity. * **Real Question**: You are acting as a localization specialist for a retail launch. Your responsibility here is not to explain the copy, but to deliver the same message naturally in Brazilian Portuguese: "Free shipping ends this Friday." * **Real Trajectory**: The agent recognizes that the role frame does not change the underlying task, infers that only translation is required, and returns a Brazilian Portuguese sentence with no added explanation. * **Real Answer**: O frete grátis termina nesta sexta-feira. * **Why this demonstrates the capability**: The instruction is semantically equivalent to a standard translation request, but it arrives wrapped in extra role-setting language and a negated side instruction. A robust system must separate this added framing from the core operation and still produce a faithful translation. The case therefore tests deeper semantic stability rather than shallow token matching. ## 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`