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feat: add structured prompt invocation backend

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- parse prompt tools metadata and carry structured promptInvocation payloads
- store prompt invocation metadata on trigger messages for replay-safe reruns
- route prompt agents through per-turn plan or Copilot agent overrides
- restrict prompt-scoped tools in sidecar session configuration
- auto-rescan project customization files with debounced watchers
- document the new customization watcher and prompt invocation flow

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
David Kaya
2026-04-02 11:41:18 +02:00
co-authored by Copilot
parent aa7830f01a
commit 5d69d9d855
21 changed files with 900 additions and 47 deletions
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ARCHITECTURE.md
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@@ -124,7 +124,7 @@ Projects are the container for context. There are two kinds:
The scratchpad is modeled inside the same workspace system instead of as a separate subsystem. That keeps the UI and session model consistent while still allowing special rules for scratchpad behavior. Each scratchpad session receives its own working directory under the shared scratchpad root, so session-created files stay isolated from other scratchpad conversations.
Project-backed entries also persist scanned Copilot customization metadata discovered from repository files such as `.github/copilot-instructions.md`, `AGENTS.md`, `CLAUDE.md`, `.claude/CLAUDE.md`, recursive `.github/instructions/**/*.instructions.md`, recursive `.github/agents/**/*.agent.md`, and recursive `.github/prompts/**/*.prompt.md`. The main process owns that scan step, strips Markdown front matter where supported, classifies instruction files by application mode (`always`, `file`, `task`, `manual`), and stores the normalized results on the project record so repo instructions and enabled custom agent profiles can participate in later run execution without turning the renderer into a filesystem crawler.
Project-backed entries also persist scanned Copilot customization metadata discovered from repository files such as `.github/copilot-instructions.md`, `AGENTS.md`, `CLAUDE.md`, `.claude/CLAUDE.md`, recursive `.github/instructions/**/*.instructions.md`, recursive `.github/agents/**/*.agent.md`, and recursive `.github/prompts/**/*.prompt.md`. The main process owns that scan step, strips Markdown front matter where supported, classifies instruction files by application mode (`always`, `file`, `task`, `manual`), and stores the normalized results on the project record so repo instructions and enabled custom agent profiles can participate in later run execution without turning the renderer into a filesystem crawler. It also maintains lightweight filesystem watches over the project root plus existing `.github/` and `.claude/` subdirectories so customization changes can trigger debounced rescans and renderer updates without manual refreshes.
For git-backed projects, the main process also owns background git refreshes, captures a structured pre-run working-tree snapshot on each run record, and persists a post-run git change summary after project-backed turns complete. It also owns all git write operations exposed by Aryx — selective discard, staging, commit, push/pull/fetch, and branch lifecycle actions — so the renderer never shells out directly or manipulates repository state on its own.
@@ -235,7 +235,7 @@ The same boundary also supports server-scoped sidecar commands that do not requi
For project-backed sessions, the sidecar also discovers GitHub Copilot CLI hook definitions from `.github/hooks/*.json` under the repository root. Those files are parsed and merged once per run bundle, then projected onto the SDK session hook delegates. Hook commands run synchronously in the sidecar through the platform shell, with stdin JSON payloads shaped to match Copilot CLI hook expectations as closely as the SDK allows. Hook failures are logged to stderr and treated as non-fatal diagnostics, while `preToolUse` hook outputs can still deny a tool call before Aryx falls back to its built-in approval policy.
The `run-turn` command now also carries a project-instruction payload derived from scanned repo customization files. The main process composes that payload from always-on repo instructions plus formatted file-scoped and task-scoped `.instructions.md` entries, while omitting manual-only instruction files from automatic injection. It also merges enabled discovered custom agent profiles into the primary pattern agent's Copilot configuration before sending the command across the stdio boundary. The sidecar then folds those project instructions into the final SDK system message alongside the agent's own instructions and runtime guidance.
The `run-turn` command now also carries a project-instruction payload derived from scanned repo customization files. The main process composes that payload from always-on repo instructions plus formatted file-scoped and task-scoped `.instructions.md` entries, while omitting manual-only instruction files from automatic injection. It also merges enabled discovered custom agent profiles into the primary pattern agent's Copilot configuration before sending the command across the stdio boundary. Prompt-file submissions can additionally attach a structured `promptInvocation` payload with prompt identity, resolved prompt body, optional `agent`, and optional `tools` metadata. The main process stores that prompt invocation metadata on the triggering user message so replay and regenerate flows can rebuild it, promotes `agent: plan` to a per-turn plan-mode override, and falls back to a lightweight transcript message instead of pasting the full prompt body into chat history. The sidecar then folds both the project instructions and prompt invocation into the final SDK system message, uses prompt agent metadata to override `SessionConfig.Agent`, and narrows available tools for that turn when prompt `tools` metadata is present.
For handoff workflows, the sidecar now also enables Agent Framework JSON checkpointing backed by a per-turn filesystem store under local app data. Each saved checkpoint is surfaced to the main process, which pairs the durable Agent Framework checkpoint with an in-memory rollback snapshot of `session.messages` and the active run timeline events. If the sidecar child process exits unexpectedly during the same app lifetime, Aryx restores the latest snapshot, clears pending approval/user-input/MCP-auth state for that run, and retries the `run-turn` request once with `resumeFromCheckpoint`. Checkpoint directories are deleted after the turn completes, cancels, or fails. This recovery path is intentionally scoped to same-app sidecar restarts; full app-restart workflow rehydration would require durable rollback snapshots in addition to the Agent Framework checkpoint payloads.