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exp(codex): surgical spinout mitigations for PRI-2672 manual App validation

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Experiment branch — NOT for merge without eval evidence (writing-skills
discipline; RED/GREEN campaign to follow if the manual run validates).

Two targeted changes against the measured Codex 5.6-era spinout
(36% of SDD runs >8h, PRI-2672):

1. codex-tools.md — SDD dispatch rules: fork_turns "none" on every
   spawn (the default "all" forks the whole transcript and refuses
   model/effort overrides — S2's terminal 13-agent final wave was all
   full-history forks at sol/xhigh); capability-check for 0.145+ spawn
   params with an explicit terra/high role table (re-review terra/medium),
   no sol seats, no effort escalation between fix rounds; honest
   inheritance warning for <=0.144 where routing is impossible (T0-probed
   on 0.144.4: schema is {task_name, message, fork_turns} only, role
   TOMLs inert).

   Role-table bet: census shows task seats already ran terra/high in the
   spinout sessions — the surgical bet is fork_turns:none + no-sol-seats
   + wave termination, not task-seat downgrade. T1 cross-review matrix
   will refine reviewer tiers (may support terra/medium or lower).

2. SKILL.md final review — wave closure is policy, not a verdict:
   strong reviewers find real defects indefinitely, so "review until
   clean" never terminates; new breakage in the final fix diff joins
   residual adjudication instead of opening wave two; one-off human
   review procedures (competing reviewers, scoring) never become
   standing. Two matching rationalization-table rows.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
Drew Ritter
2026-07-21 12:36:50 -07:00
parent cc690476fc
commit 3921dc9998
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11
skills/subagent-driven-development/SKILL.md
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@@ -413,6 +413,15 @@ rulings, or stop on load-bearing ones. There is no second fix wave —
residual load-bearing findings surface to your human partner when
finishing-a-development-branch presents the options.
The wave closing is policy, not a verdict. A sufficiently strong reviewer
finds real defects indefinitely, so "review until one comes back clean"
never terminates — the completed wave is the exit, not a clean report.
New Critical/Important breakage in the final fix diff joins the residuals
for adjudication; it does not start a second wave. And review procedures
your human partner sets up for one review — competing reviewers, scoring,
extra seats — apply to that review only. Never adopt them as standing
procedure for reviews they didn't ask about.
## Finish
When the final whole-branch review is clean and its fixes are merged,
@@ -434,6 +443,8 @@ Use superpowers:finishing-a-development-branch.
| "The fix was small, skip the re-review" | Unreviewed fixes are how regressions land. Every round ends with a scoped re-review. |
| "Reviews slow the loop down" | The loop without reviews is just unverified churn. Reviews are the loop's brakes and steering. |
| "Ledger bookkeeping is overhead" | The ledger is what survives compaction. Controllers without one have re-dispatched entire completed task sequences. |
| "This new finding is real — one more wave" | Real findings are infinite under a strong reviewer. The completed wave is the exit; adjudicate and route. |
| "They liked competing reviewers earlier, I'll run them again" | One-off review procedures apply to the review they were given for. Re-adopting them unasked is scope creep in review clothing. |
## Example Workflow

41
skills/using-superpowers/references/codex-tools.md
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@@ -9,6 +9,47 @@ multi_agent = true
This enables `spawn_agent`, `wait_agent`, and `close_agent` for skills like `dispatching-parallel-agents` and `subagent-driven-development`. When using subagent-driven-development, close reviewer subagents when their review returns. Keep each implementer subagent open until its task's review passes — the fix loop resumes the implementer — then close it. If your harness cannot send another message to a spawned agent, dispatch each fix round as a fresh implementer carrying the brief, the report file, and the findings.
## SDD dispatch: pin fork_turns and the model on every spawn
Every `spawn_agent` call in subagent-driven-development sets
`fork_turns: "none"`. The parameter defaults to `"all"`, which forks your
entire session transcript into the child — the opposite of the fresh,
constructed context SDD requires — and a full-history fork also refuses
model and effort overrides. Never omit the parameter, and never pass
`"all"` or a turn count for an SDD dispatch.
Before Task 1, check your `spawn_agent` tool schema for `model` and
`reasoning_effort` parameters (present on Codex 0.145+).
**If the parameters exist**, set both explicitly on every dispatch:
| Role | model | reasoning_effort |
|------|-------|------------------|
| Implementer (all rounds) | `gpt-5.6-terra` | `high` |
| Task reviewer | `gpt-5.6-terra` | `high` |
| Scoped re-review | `gpt-5.6-terra` | `medium` |
| Final whole-branch review | `gpt-5.6-terra` | `high` |
On Codex this table IS the Model Selection mapping — including the final
review, which stays on terra/high rather than "most capable available."
Never give a subagent your session's model when you run a frontier config
(sol at xhigh or max): reviewer tier never exceeds implementer tier, and
a fix round never gets an effort bump. Rounds 4-5's "more capable model"
means a fresh implementer at the same tier; a task that genuinely needs
more than terra/high is a BLOCKED escalation to your human partner, not
a quiet tier climb. Frontier-tier subagents at inherited effort are the
measured top driver of Codex SDD runs spinning out to 8+ hours
(PRI-2672): review seats that inherited sol found real-but-endless
defects every round, and fix diffs ballooned instead of converging.
**If the parameters do not exist** (Codex 0.144 and earlier), every child
inherits your session's model and effort and no override is possible —
role files in `~/.codex/agents/` do not attach to spawns either. Say so
to your human partner before starting a plan of more than a few tasks,
and offer the choice: proceed with inheritance, or restart the session
at a lower effort so the whole run — controller and children — pays the
lower rate.
## Environment Detection
Skills that create worktrees or finish branches should detect their