What it is
Real prompts I wrote while steering coding agents on my own projects in this domain. Each record pairs the prompt with the agent's next actions (tool calls, where the harness recorded them) and my following turn, so the data shows how a human corrects, redirects and approves an agent over a long session.
Size and period
| Prompts | 1,504 |
| Sessions | 29 |
| Period | Feb 2026 to Oct 2026 |
| Harnesses | Codex (968), Claude Code (535), Codex (OpenRouter) (1) |
| With the agent's tool calls | 1,497 prompts |
| Projects it spans | 7 |
What it is good for
- Training and evaluating agents doing weight-space work: reading tensors, patching safetensors, merging and pruning models.
- Studying how an experienced engineer steers agents: corrections, scope changes, approvals.
- Building reward models or graders for agent behaviour from real human follow-ups.
What is left out
- Model-written text of any kind: no agent replies, only my prompts and the agent's tool-call metadata.
- Client work, job applications and personal folders.
- Secrets and personal data: scrubbed by rules, then by a local privacy model as a second pass.
How to license it
Non-exclusive, per pack, directly with me or through DataVendor. Ask for the datasheet and a 25-record sample first.