[aw] Fix Bug from Labeled Issue exceeded max AI credits

### Workflow Failure

**Workflow:** [Fix Bug from Labeled Issue](https://github.com/github/spec-kit/blob/main/.github/workflows/bug-fix.md)
**Branch:** main
**Run:** https://github.com/github/spec-kit/actions/runs/34245344272
**Pull Request:** [#2884](https://github.com/github/spec-kit/pull/2884)

> [!WARNING]
> **AI Credits Budget Exceeded**
>
> The workflow hit the configured `max-ai-credits` guardrail. Used `1K` of `1K` max (over by `8.4`).

Increase the limit

Update `max-ai-credits` in your workflow frontmatter:

```yaml
max-ai-credits: 2000
```

Tips for reducing AI credit usage

- Review the [cost optimization guidance](https://github.github.com/gh-aw/reference/cost-management/).
- Reduce unnecessary model or tool calls in the prompt.
- Trim large inputs or excess context that does not change the outcome.
- Split large tasks across smaller runs when possible.

> [!WARNING]
> **Task Could Not Be Completed**: The agent reported that the task could not be performed due to an infrastructure or tool failure.

**Reasons:**
- The requested pytest command could not start: the execution environment returned “Permission denied and could not request permission from user.”

Command attempted: ./.venv/bin/python -m pytest -q tests/integration/test_bundler_install_flow.py tests/integration/test_bundler_init_install.py tests/integration/test_bundler_local_install.py tests/integration/test_bundler_offline.py

No tests ran, so pass/fail counts are unavailable. No repository files were modified.

This is a structured incompletion signal (`report_incomplete`), not a real task outcome. Any other safe outputs emitted alongside this signal (e.g., comments) describe the failure state, not a completed review or action.

> [!WARNING]
> **Engine Failure**: The `copilot` engine terminated unexpectedly.

**Last agent output:**
```
│ src/specify_cli/workflows/_commands.py tests/bundler_helpers.py
│ tests/integration/test_bundler_install_flow.py
│ tests/unit/test_bundler_primitives.py && git --no-pager status --short …
└ 11 lines...
● search_issues (MCP: github) · is:pr is:open author:mnriem · owner: "mnriem", repo: "spec-kit", qu…
└ [{"content":[{"text":"{\"total_count\":0,\"incomplete_results\":false,\"...
Failed to get response from the AI model; retried 5 times (total retry wait time: 94.71 seconds) (Request-ID 7539ecf4-d237-4f2f-8248-9ae909d6335e) Last error: CAPIError: 429 Maximum AI credits exceeded (1008.399375 / 1000).
Changes +276 -43
Duration 16m 25s
Tokens ↑ 7.7m (7.4m cached) • ↓ 43.7k (25.1k reasoning)
```

### Action Required

**Assign this issue to an agent** to debug and fix the issue.

Debug with any coding agent

Use this prompt with any coding agent (GitHub Copilot, Claude, Gemini, etc.):

````
Debug the agentic workflow failure using https://raw.githubusercontent.com/github/gh-aw/main/debug.md

The failed workflow run is at https://github.com/github/spec-kit/actions/runs/34245344272
````

Manually invoke the agent

Debug this workflow failure using your favorite Agent CLI and the `agentic-workflows` prompt.

- Start your agent
- Load the `agentic-workflows` skill from `.github/skills/agentic-workflows/SKILL.md` or
- Type `debug the agentic workflow bug-fix failure in https://github.com/github/spec-kit/actions/runs/34245344272`

> [!TIP]
>
> Stop reporting this workflow as a failure
>
> To stop a workflow from creating failure issues, set `report-failure-as-issue: false` in its frontmatter:
> ```yaml
> safe-outputs:
> report-failure-as-issue: false
> ```
>
>

> Generated from [Fix Bug from Labeled Issue](https://github.com/github/spec-kit/actions/runs/34245344272) · 1K AIC · [◷](https://github.com/search?q=repo%3Agithub%2Fspec-kit+is%3Aissue+%22gh-aw-workflow-id%3A+bug-fix%22&type=issues)
> - [x] expires on Sep 15, 2026, 3:53 PM UTC

Start with .github/workflows/bug-fix.md and the failed run, then inspect src/specify_cli/workflows/_commands.py and tests/bundler_helpers.py. Run the listed integration tests in tests/integration and review tests/unit/test_bundler_primitives.py; done means the workflow no longer fails on its reported credit or execution errors and the tests can run.

Written by the indexing model from the issue text.