围绕Identical这一话题，市面上存在多种不同的观点和方案。本文从多个维度进行横向对比，帮您做出明智选择。
维度一：技术层面 — The same tension exists in the agent context file space. We don't need CLAUDE.md and AGENTS.md and copilot-instructions.md to converge into one file. We need them to coexist without collision. And to be fair, some convergence is happening. Anthropic released Agent Skills as an open standard, a SKILL.md format that Microsoft, OpenAI, Atlassian, GitHub, and Cursor have all adopted. A skill you write for Claude Code works in Codex, works in Copilot. The file format is the API.
维度二：成本分析 — The BrokenMath benchmark (NeurIPS 2025 Math-AI Workshop) tested this in formal reasoning across 504 samples. Even GPT-5 produced sycophantic “proofs” of false theorems 29% of the time when the user implied the statement was true. The model generates a convincing but false proof because the user signaled that the conclusion should be positive. GPT-5 is not an early model. It’s also the least sycophantic in the BrokenMath table. The problem is structural to RLHF: preference data contains an agreement bias. Reward models learn to score agreeable outputs higher, and optimization widens the gap. Base models before RLHF were reported in one analysis to show no measurable sycophancy across tested sizes. Only after fine-tuning did sycophancy enter the chat. (literally)
据统计数据显示，相关领域的市场规模已达到了新的历史高点，年复合增长率保持在两位数水平。
维度三：用户体验 — CLI-based ticket tracking seems to be a necessity to support driving multiple agents at once, for long periods of time, and to execute complex tasks. A bunch of tools have shown up to track tickets via Markdown files in a way that the agents can interact with.
维度四：市场表现 — "useSsl": false,
展望未来，Identical的发展趋势值得持续关注。专家建议，各方应加强协作创新，共同推动行业向更加健康、可持续的方向发展。