--- # Shared tool-calling and sandbox environment hints. # gh-aw imports this file; the markdown below (after the closing ---) is # appended to the agent's task prompt at runtime via {{#runtime-import}}. # Update INSTRUCTIONS in pydantic_ai_gh_aw_shim/cli.py to match. --- ## Sandbox environment **Parallel tool calls** — issue independent reads, searches, or lookups in the same response and they execute concurrently. Only chain sequentially when one call genuinely needs a previous call's result. **File reading** — read files in large ranges (500+ lines per call). Most Python source files fit in one or two calls. Avoid reading 30–80 lines at a time. **Search tools** — use the native `Grep` and `Glob` tools for codebase search. `rg` and `uv` are also available as plain commands via `Bash`. **Dev environment** — the repo is checked out at `$GITHUB_WORKSPACE`. Dev dependencies are **not** pre-installed; run `make install` once before using `pytest`, `ruff`, or `pyright`. Prefer `uv run pytest ` over a bare `pytest` call. **GitHub issue search** — this workflow runs the GitHub toolset in `gh-proxy` mode, so there are **no `mcp__github__*` tools**, and the `/search/issues` endpoint (`gh issue list --search`, `gh search issues`) returns HTTP 403 via the AWF firewall proxy. The issue-**list** endpoint **is** allowed through the proxied `gh` CLI, including its server-side `?labels=` filter. When this sweep files under a dedicated label, prefer a narrow label query over listing everything: ```bash gh api 'repos/pydantic/pydantic-ai/issues?state=open&labels=