[Parent] Track and resolve recurring AI-credits rate-limit failures in scheduled agentic workflows

Scheduled agentic workflows (Issue Arborist, Dependency Version Updater, and others) are repeatedly hitting the AI-credits rate limit, causing failed or incomplete pipeline runs. These failures have accumulated into 7+ separate incident issues since they share a common root cause.

## Related incident reports
- #1515 — Issue Arborist hit AI credits rate limit
- #1492 — Dependency Version Updater hit AI credits rate limit
- #1478 — Dependency Version Updater hit AI credits rate limit
- #1467 — Issue Arborist hit AI credits rate limit
- #1441 — Dependency Version Updater hit AI credits rate limit
- #1430 — Issue Arborist hit AI credits rate limit
- #1412 — Dependency Version Updater hit AI credits rate limit

## Potential mitigations
- Reduce token usage per agent run (tighter prompts, shorter context)
- Stagger or reduce schedule frequency
- Investigate whether model selection affects credit consumption
- Add retry/backoff strategy when rate-limited rather than failing immediately
- Surface credit-usage telemetry in `ado-aw audit` for ongoing monitoring

> Generated by [Issue Arborist](https://github.com/githubnext/ado-aw/actions/runs/29449185408) · 44.2 AIC · ⌖ 6.15 AIC · ⊞ 6K · [◷](https://github.com/search?q=repo%3Agithubnext%2Fado-aw+is%3Aissue+%22gh-aw-workflow-call-id%3A+githubnext%2Fado-aw%2Fissue-arborist%22&type=issues)

Review the seven linked incident issues and scheduled workflow runs to compare where AI-credit limits occur; inspect `ado-aw audit` as the named monitoring entry point. Define and validate a mitigation involving usage, scheduling, model selection, or retry/backoff, with credit consumption observable and recurring failures no longer causing incomplete runs.

Written by the indexing model from the issue text.