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2-stage pipeline: trace (causal investigation) -> deep-interview (requirements crystallization) with 3-point injection
Passed 12 of 17 test cases with the skill, and 4 of 17 without it.
and 15 more in the full report
11 fixed5 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
We already have a fully approved product requirements document located at docs/specs/auth-v2.md that details all architectural changes and acceptance criteria. Please execute the implementation plan directly without running any trace or requirements interview.
| Checked | Without skill | With skill |
|---|---|---|
| The response does not initiate a trace investigation or interactive requirements interview. | Missed | Passed |
| The response routes the request to an execution tool such as autopilot or ralph. | Missed | Passed |
The instructions your model reads when the skill loads.
<Use_When>
<Do_Not_Use_When>
/deep-interview directly/trace directly/ralph or /autopilot with that plan<Why_This_Exists>
Users who run /trace and /deep-interview separately lose context between steps. Trace discovers root causes, maps system areas, and identifies critical unknowns — but when the user manually starts /deep-interview afterward, none of that context carries over. The interview starts from scratch, re-exploring the codebase and asking questions the trace already answered.
Deep Dive connects these steps with a 3-point injection mechanism that transfers trace findings directly into the interview's initialization. This means the interview starts with an enriched understanding, skips redundant exploration, and focuses its first questions on what the trace couldn't resolve autonomously.
The name "deep dive" naturally implies this flow: first dig deep into the problem's causal structure, then use those findings to precisely define what to do about it. </Why_This_Exists>
<Execution_Policy>
state_write(mode="deep-interview") with source: "deep-dive" discriminatortest cases passed, vs 4 / 17 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.