Real-time thinking chain trajectory analysis of DeepSeek Harness

Project overview

Real-time chain-of-thought trajectory profiling for DeepSeek Harness: watch the reasoning stream as it happens, tally signature wording indicators (let me / we / let's / I), classify the current session's trajectory family against built-in baselines, and optionally record per-session measurement aggregates. Read this first: honest framing

Wording fingerprints describe the (model × assembly) combination — system prompt, tool schema, reasoning effort — not model identity. The underlying research (xiaobright/modeltest) shows the same wording pattern across different models when the interface changes (the V4 Flash counterexample: identical we-heavy, let me-free reasoning under the minimal assembly, at a different ability level).

yjh051108/dsh-router-standard maps the same lexicon onto a fault line: along the persona axis, V4 Pro behavior collapses into three bands — spec (collective We, let me ≈ 0), a transition band (mixed: We/The/Let mixing, unstable), and react (first-person The/Let, we ≈ 0). Neither side is universally "stronger" (maintenance tasks favor the spec side; greenfield builds favor the react side). The author's own correction note rejects any reading of the wording as