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feat(coding-agent): removed context argument from eval agent() spawn

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Shared background now flows through a '/Users/can/.omp/agent/sessions/-Projects-.tree-pi-commit/2026-06-10T15-36-32-782Z_019eb22d-970e-7000-8964-72c98becf3e8/local' file referenced in each prompt instead of a context string forwarded into the subagent's system prompt. The JS and Python preludes drop the context kwarg from agent(), the subagent system prompt drops the {{#if context}} block and the conversation-context file pointer, and runEvalAgent no longer writes a per-call conversation context file. AgentSession sheds the now-unused formatCompactContext() helper that supplied the file's body, and ToolSession.getCompactContext is removed alongside it.
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can1357
2026-06-10 17:49:01 +02:00
parent fcb8663de8
commit a92d2ce989
10 changed files with 19 additions and 113 deletions
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docs/tools/eval.md
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@@ -138,7 +138,7 @@ Implemented in `packages/coding-agent/src/eval/js/worker-core.ts`, `packages/cod
- `await read(path, { offset?, limit? })`
- `await tree(path = ".", { maxDepth?, hidden? })`
- `sort(text, { reverse?, unique? })`, `uniq(text, { count? })`, `counter(items, { limit?, reverse? })`
- `await agent(prompt, { agentType?, model?, context?, label?, schema? })`
- `await agent(prompt, { agentType?, model?, label?, schema? })`
- `await parallel([() => agent("a"), () => agent("b")])`
- `await pipeline(items, stage1, stage2)`
- `display(value)` behavior:
@@ -192,11 +192,11 @@ Both runtimes expose `completion()` — a single stateless completion against a
Both runtimes expose `agent()` — a single subagent invocation routed through `packages/coding-agent/src/eval/agent-bridge.ts` into the same `runSubprocess(...)` path used by the `task` tool. It uses the current eval session's spawn policy and inherits the parent eval executor id, so parent and subagent code share JS/Python runtime state.
- Signatures:
- JS: `await agent(prompt, { agentType?, model?, context?, label?, schema? })`
- Python: `agent(prompt, *, agent_type="task", model=None, context=None, label=None, schema=None)`
- JS: `await agent(prompt, { agentType?, model?, label?, schema? })`
- Python: `agent(prompt, *, agent_type="task", model=None, label=None, schema=None)`
- `agentType` / `agent_type` defaults to the bundled `task` agent and resolves through normal agent discovery, so project and user agents work.
- `model` overrides the selected agent's model. Without it, normal per-agent settings and the agent frontmatter model apply.
- `context` supplies shared background; `label` controls the `agent://<id>` output label prefix.
- Shared background is passed via files: write a `local://` file and reference it in the prompt. `label` controls the `agent://<id>` output label prefix.
- `schema` passes a JSON Schema to the subagent structured-output path. When present, the helper parses the final JSON text and returns an object.
- Spawn restrictions use `session.getSessionSpawns()` exactly like the `task` tool. Eval-driven subagent recursion is capped at depth 3.
- JS and Python both expose `parallel(thunks)` and `pipeline(items, ...stages)`; both use a bounded async/threaded pool whose width tracks the `task.maxConcurrency` setting (the same ceiling the `task` tool uses; `0` = run every item at once), preserve item order, and propagate rejections. The width is fetched live from the host via the `__concurrency__` bridge, so the helpers no longer take a `concurrency` argument.