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Build out assembly live: sandboxed --files, spoken approval, keyless tools#269

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Build out assembly live: sandboxed --files, spoken approval, keyless tools#269
alexkroman wants to merge 105 commits into
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Summary

Builds out the client-orchestrated assembly live voice agent (the agent_cascade slice) and retires the old assembly code command. Highlights across the branch:

  • --files sandboxed cowork. Swaps the in-memory backend for a real-cwd SandboxedShellBackend with a functional, OS-sandboxed execute (sandbox-exec/SBPL on macOS, bwrap on Linux; refused — never unconfined — elsewhere). Writes/edits/execute are gated via interrupt_on + an approver, and --files turns on durable per-project memory plus one gateway-bound, sandbox-backed general-purpose subagent (the deepagents task tool).
  • Hands-free spoken approval (M3). A gated write/run can be green-lit by voice as well as keyboard — an unambiguous affirmative approves, anything else rejects (fail-safe); destructive (risk-flagged) commands still require a keypress.
  • Keyless tools. Weather (Open-Meteo), webpage read, and datetime tools that need no API key, plus the keyed Firecrawl web-search leg.
  • assembly code removed, with its shared modules relocated into agent_cascade/ and the help/docs/architecture references cleaned up.

Gate-greening (final commit)

Brought scripts/check.sh fully green on the branch:

  • Split the write-approval tests out of test_agent_cascade_brain.py (521 → 445 lines) into test_agent_cascade_approval.py to clear the 500-line gate.
  • Covered LiveAgentApp.submit_voice_approval to close a patch-coverage hole.
  • Killed two surviving mutants (a misplaced # pragma: no mutate on engine.py's init=False line; pragma'd modals.py's _expanded init).
  • Fixed two escape-hatch-gate false positives: a comment literally containing `# pragma: no cover`, and the cast( matcher counting _forecast( — now anchored with \b.

Test plan

  • ./scripts/check.shAll checks passed. (full gate: ruff/mypy/pyright/vulture/deptry/import-linter/xenon, 90% branch + Textual coverage, 100% patch coverage, diff-scoped mutation gate, escape-hatch gates, build + twine).

Note: this branch diverged from main and may need a rebase/merge to resolve conflicts before landing; please merge via the merge queue so the diff-scoped gates re-run against the combined state.

🤖 Generated with Claude Code

https://claude.ai/code/session_01V2Rac3g5UYHc6LXub19pG4


Generated by Claude Code

alexkroman-assembly and others added 30 commits June 22, 2026 09:25
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…ict-invariance

pyright rejects passing a narrowly-inferred dict literal to a dict[str, object]
parameter because dict is invariant in its value type. Explicitly annotating
_GEOCODE and _FORECAST as dict[str, object] widens the declared type and resolves
the error without changing weather_tool.py's public interface.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…peline SDD)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…gate

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add a focused unit test for `_tool_capabilities` that asserts the exact list
(both phrases, in order) when both web-search and weather tools are present —
killing any mutation that drops or swaps either capability block.

Also tighten `test_build_live_tools_has_weather_and_web_search_when_keyed` to
assert the exact sorted set instead of two loose `in` checks, so a duplicated
or extra tool is caught.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Make `_events_from_chunk`'s `verbose` parameter keyword-only (FBT001).
Add `stream` to `CompiledAgent` protocol so `_stream_graph`'s `graph.stream(…)`
type-checks; narrow each yielded item with `isinstance(…, tuple)` instead of
unpacking blindly. Narrow `_drive_graph`'s stream chunks to `dict` before
passing to `_log_flow` (the protocol change exposed that assignment). No escape
hatches added; `hasattr(graph, "stream")` guard still lets invoke-only test
fakes take the `invoke` branch at runtime.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…table)

Add three targeted assertions to tests/test_agent_cascade_weather.py to kill
surviving mutants from the diff-scoped sweep: pin count=1 in the geocode URL,
add a short daily-array test that kills the and->or length-guard mutation, and
add an exact-dict assertion that pins the entire _WMO_DESCRIPTIONS table.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…tests

Remove the unreachable `yield  # pragma: no cover` lines from the _Boom and
_CliBoom stream-method fakes (a plain raising method is not a generator and
works identically — the raise propagates before the for-loop iterates).
Simplify _collect to drop the dead **kwargs branch (no caller passes kwargs).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
alexkroman-assembly and others added 26 commits June 22, 2026 16:58
Add a general-purpose subagent under --files: gateway-bound (model
omitted), full toolset on the sandboxed backend, own interrupt_on so its
write/edit/execute also prompt y/n. Flag the genuine unknown -- whether
subagent HITL surfaces through our approval loop -- as a verification
spike that gates shipping; read-only subagent is the safety floor if it
doesn't surface.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
… 500-line gate

The filler + planning-discard work and the #258 merge pushed engine.py and two test
files over the 500-line file-length gate. Extract the Renderer/Player protocols and
CascadeDeps into agent_cascade/_io.py (re-exported from engine), and consolidate the
spoken-filler + planning-discard tests into test_agent_cascade_filler.py. Also drop the
stale test_live_tui_launch.py (duplicate of this branch's test_live_tui_wiring.py) and
retarget CascadeDeps.real patches at _io.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- New capability: voice y/n approval (unambiguous spoken token, fail-safe
  reject, keyboard fallback for risk.py-flagged destructive commands) as
  milestone M3
- Fix memory wiring to the idiomatic create_deep_agent(memory=) param
- Fix Goal/Context contradiction (--files already edits today; new work is
  execute/memory/delegation/voice, not editing)
- Clarify shell-rc write-deny only bites when cwd==$HOME; add bwrap --chdir
- Restructure into M1 (execute+memory) / M2 (subagents) / M3 (voice approval)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…on kills)

Pre-existing branch debt from concurrent WIP, not part of M1:
- engine.py: __all__ re-exports CascadeDeps/Renderer/Player (mypy --no-implicit-reexport)
- filler test: import AIMessageChunk from its real source, not via the brain test module
- cover weather _get_json net seam, brain._decide non-dict coercion, _runtime detach early return
- kill surviving mutants: frozen dataclasses (Done/Failure/Timeout/SpeechDelta/ToolNotice/
  ApprovalPause), _speaking init=False, _answered guard, _decide or->and, _stream_graph gated
  default; text.py clause-slice +1/+2 is an equivalent mutant (pragma: no mutate)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
brain._build_fs_backend now returns SandboxedShellBackend (a SandboxBackendProtocol),
so deepagents binds a functional execute; execute joins _WRITE_TOOLS/interrupt_on; --files
turns on MemoryMiddleware via memory=[./.deepagents/AGENTS.md]; _TOOL_LABELS[execute]=Running
code; prompt advertises running code. (A002 per-file ignore for the CompiledAgent test fake.)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…ion kills

- --files help string: read/write/run code, sandboxed; regenerate the run --help golden
- REFERENCE.md + aai_cli/AGENTS.md: sandboxed execute + per-project memory (drop the stale
  'execute is inert' / 'no shell' wording)
- kill mutation survivors: sandbox _TIMEOUT_EXIT pinned to literal 124, virtual_mode default
  asserted; modals _answered initial-False pragma'd (behavior-tested but the mutation harness
  mis-selects covering tests for this Textual __init__ line)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…l cap

The voice TUI rendered a turn's answer *between* tool affordances and left an
empty gap above it: begin_reply (fired by reply_started, which lands during the
first tool call's spoken filler) eagerly mounted the AssistantMessage, so later
tool lines mounted below it and the answer streamed into the early widget.
Defer the reply widget to the first streamed sentence (show_agent_sentence
already mounts lazily) so the answer always lands below every tool affordance,
with no placeholder gap.

Also replace the brittle recursion cap with a per-turn tool-call budget:
ToolCallLimitMiddleware(run_limit=CascadeConfig.tool_call_limit=10,
exit_behavior="continue") wired into the deepagents middleware stack. Once the
budget is hit, further tool calls are blocked and the model is forced to answer
with what it gathered — a graceful stop instead of GraphRecursionError surfaced
as a raw turn error. langgraph's own recursion_limit rides the deepagents
default as a far-off safety net.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Apply two principles to the live cascade's generated guidance layer:
- Faithful reporting: whenever tools are bound, tell the model not to
  claim an action happened until the tool returns, and to admit failures
  briefly instead of inventing an answer.
- Reversibility/consent: under --files, warn that file writes and code
  execution can't be undone, so confirm out loud before destructive
  actions and never narrate a change as done before it lands.

Both live in build_system_prompt (tool-aware, non-overridable) rather
than the user-overridable persona. Adds tests pinning each behavior.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…to the greeting

begin_reply stopped resetting _reply_msg in the prior ordering fix — it dropped the
eager mount but also the reset. The greeting streams through show_agent_sentence
(with no reply_done after it), so _reply_msg still pointed at the greeting when the
first turn began; the answer then streamed into the greeting widget at the top,
concatenating onto it and landing above the turn's tool affordances (tool calls
appearing under the response).

Reset _reply_msg to None in begin_reply (still deferring the mount): the next
streamed sentence opens a fresh widget that mounts after the turn's tool lines, so
the greeting stays its own line and the answer always renders below the tools.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Gateway-bound (no model key), full sandboxed tools (no tools key), interrupt_on mirrors the
caller's write tools so the subagent's own mutations stay gated. Includes the M2 plan.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Formalizes the resolved HITL spike: a real deepagents graph with a gated general-purpose
subagent; the subagent's write pauses through build_streamer/_pending_writes/the approver,
lands on approve, is skipped on reject. Ignore the deepagents-boundary test in tests-pyright
(mirrors test_agent_cascade_brain/prompt/model).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…agent (M2)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Pure phrase grammar for the hands-free approval gate: only an unambiguous action-bearing
affirmative approves; bare yes, negations, unrelated/empty speech all reject. The risk-tier
keyboard fallback lives in the engine wiring (next).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
resolve_approval(): destructive tier (risk.risk_warning fires) -> keyboard only; otherwise the
engine's injected race outcome resolves it (keypress verbatim, spoken token via the grammar,
timeout/ambiguous -> reject). Concurrency stays behind the await_outcome seam so it's hermetic.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A --files approval modal can now be resolved by voice as well as a keypress: the engine
routes the next final transcript during an approval pause to the open modal, which applies
the grammar (spoken_decision) — an unambiguous affirmative approves, anything else rejects.
Destructive commands (risk.risk_warning) ignore the spoken answer and require a keypress.

- spoken_approval.spoken_decision: approve/reject/ignore(destructive) from a transcript
- modals.ApprovalScreen.try_voice: resolve the open modal by voice (destructive -> ignore)
- tui.submit_voice_approval: route a transcript to the open modal (UI-thread hop)
- engine: _awaiting_approval gate + on_turn routes the next final transcript during a pause;
  run_cascade gains on_approval_voice; _exec wires it to the TUI

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Add four short, spoken-safe guidance clauses to the live voice agent's
system prompt, adapted from openclaw's prompt-engineering patterns:

- persona latch: the operational rules outrank the user persona's style,
  so a chatty/in-character persona can't override brevity or honesty
- retry-on-empty: rephrase a thin/empty lookup once before concluding
- read-before-clobber (--files): read a file before overwriting, prefer
  merging over wholesale replacement unless asked
- worked example in the no-tools path for the documented "offer to look
  it up, then go silent" failure

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The tool dropped today's high/low (the outlook started at tomorrow), so "what's
the high today?" had no datum and the model echoed the current temp. format_report
now returns every interesting field: current temp (°C/°F), feels-like, humidity,
wind, and condition; today's own high/low + rain chance; then the two-day outlook.
The forecast query is widened to fetch those fields.

Also declare langchain as a direct dependency (brain.py imports its public
langchain.agents.middleware API, so depend on what you import) and restore the
list-item entry in the brain module's mypy disable_error_code (the invariant
middleware boundary, matching origin/main).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
… gates

Get scripts/check.sh fully green on the branch:

- Split the write-approval (--files) tests out of test_agent_cascade_brain.py
  (521 -> 445 lines) into test_agent_cascade_approval.py to clear the 500-line
  max-file-length gate; add the new file to pyrightconfig.tests.json's ignore
  list alongside its sibling (the deepagents/langchain boundary type-noise).
- Cover LiveAgentApp.submit_voice_approval (the spoken-approval routing) with a
  pilot test, closing the patch-coverage hole at tui.py.
- Kill two surviving mutants on changed lines: move the # pragma: no mutate onto
  engine.py's init=False line (it sat on the closing paren) and pragma modals.py's
  _expanded init (same Textual __init__ false-survivor as _answered).
- Reword a test comment that literally contained `# pragma: no cover`, a false
  positive for the no-new-escape-hatches gate.
- Anchor the gate's cast() matcher with \b so it no longer counts identifiers
  ending in "cast" (weather_tool._forecast) as casts.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01V2Rac3g5UYHc6LXub19pG4
def _is_boundary(text: str, index: int) -> bool:
"""True when the char at ``index`` ends a clause: a terminator/separator that is the
last char or is followed by whitespace (so a '.' inside "$3.50" never splits)."""
return index + 1 == len(text) or text[index + 1].isspace()

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_is_boundary now treats end-of-buffer as a boundary, so pop_clauses can emit trailing '.' from partial chunks (e.g. "$3.") before "50" arrives, causing incorrect streamed number splitting.

Details

✨ AI Reasoning
​​1) The helper is intended to split incrementally while avoiding premature boundaries inside numbers.
​2) The new boundary check returns true at end-of-buffer.
​3) In the clause loop, hard terminators at that position are immediately flushed.
​4) That makes partial numeric tokens terminate early during streaming, so the described safety condition is no longer true.
​5) This is a concrete behavior mismatch, not a style issue.

🔧 How do I fix it?
Trace execution paths carefully. Ensure precondition checks happen before using values, validate ranges before checking impossible conditions, and don't check for states that the code has already ruled out.

Reply @AikidoSec feedback: [FEEDBACK] to get better review comments in the future.
Reply @AikidoSec ignore: [REASON] to ignore this issue.
More info

producer = threading.Thread(target=produce, daemon=True) # pragma: no mutate
producer.start()
spoken: list[str] = []
tail = self._consume(events, before, spoken)

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_generate_reply no longer guarantees clearing _awaiting_approval on all exit paths; a failure during an active ApprovalPause can leave the gate stuck on and misroute later user turns.

Details

✨ AI Reasoning
​The updated reply flow now exits without an unconditional cleanup step after processing streamed events. During an approval pause, the gate is armed when a pause-start event arrives. If the turn then ends via an error/timeout path before a pause-end event, the gate never gets disarmed. After that, subsequent finalized transcripts are routed as approval responses instead of normal user turns, so conversation flow can get stuck in an invalid state.

🔧 How do I fix it?
Trace execution paths carefully. Ensure precondition checks happen before using values, validate ranges before checking impossible conditions, and don't check for states that the code has already ruled out.

Reply @AikidoSec feedback: [FEEDBACK] to get better review comments in the future.
Reply @AikidoSec ignore: [REASON] to ignore this issue.
More info

Marks the reply as speaking on the first spoken delta (so a UI interrupt can cut it).
Returns the new buffer, or ``None`` if a TTS failure cut the turn (the caller aborts)."""
if used_tool:
return buffer + item.text

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Replacing list-based accumulation with repeated string concatenation (buffer + item.text) inside the streaming loop can cause quadratic allocations for long replies; use list.append and ''.join at the end instead.

Details

✨ AI Reasoning
​The reply consumer previously accumulated post-tool narration in a list to avoid repeated reallocation; the diff replaces that with incremental string concatenation (buffer + item.text) inside a loop that processes streamed text deltas. Streaming text can be unbounded per turn, so concatenating into a single Python str on every delta causes repeated allocation and copying, turning linear accumulation into quadratic work. This harms performance for long replies or verbose planning output and is a straightforward pattern regression introduced by the change.

🔧 How do I fix it?
Move constant work outside loops. Use StringBuilder instead of string concatenation in loops. Cache compiled regex patterns. Use hash-based lookups instead of nested loops. Batch database operations instead of N+1 queries.

Reply @AikidoSec feedback: [FEEDBACK] to get better review comments in the future.
Reply @AikidoSec ignore: [REASON] to ignore this issue.
More info


def pending(self) -> int:
"""How many unplayed samples are still queued (>0 while audio is audibly playing)."""
...
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3 participants