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The idalib worker is the only backend now, so remove the dead HTTP/supervisor
surface entirely (~2200 lines):
* deleted idatui/client.py (the IDAClient HTTP/JSON-RPC transport + session
manager), idatui/tui.py (the old mcp TUI entry, superseded by launch.py),
spawn.sh, and systemd/ (the supervisor unit).
* deleted the mcp-only tests (stress_client, smoke_client, test_keepalive,
stress_paging, rpc_smoke, serverctl.sh, pane_smoke, test_domain) -- the worker
pilot (tests/test_scenarios.py) supersedes them.
* migrated the tmux RPC harness (idatui/pane.py) to the worker: it spawns
`idatui.launch <binary> --rpc <sock>` instead of the mcp `idatui.tui`, drops
the supervisor auto-start/ensure machinery, and reaps our own worker
(idatui/worker.py) instead of ida_pro_mcp.idalib_server. --db/--url/--no-
ensure-server are gone; --open is required.
* __init__ / __main__ / domain no longer import client (exceptions come from
errors.py, the domain client hint is WorkerClient); pyproject points both
console scripts at idatui.launch; README + ida-tui header describe the
worker-only flow.
What stays (by design): the ida_pro_mcp *package* (the worker reuses its @tool
functions in-process) and server/patch_server.py (the worker injects its custom
tools on startup). Verified: whole package imports + IdaTui constructs + pilot
lists 31 scenarios. The worker pilot (134 pass / 2 known flakes) is the E2E gate.
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Measured against libcrypto.so.3 (10,092 funcs, biggest 52,120 insns):
- list_* count cap ~700, disasm max_instructions cap ~500, then SILENT
collapse to 10 (not clamped) -> must clamp client-side (use 500).
- pagination must advance by len(data); next_offset=offset+count skips data.
- disasm offset paging is O(offset): 6ms@0 -> 180ms@50k, no resumable cursor
-> domain layer must cache windows + prefetch + over-fetch.
- include_total scans whole func (~217ms on monster) -> fetch once, cache.
- decompile hard-fails on huge funcs as a soft error (code=null) -> handle.
- idb_open needs a writable path for the .i64.
tests/stress_paging.py: durable paging benchmark harness
docs/PAGING_FINDINGS.md: constraints that drive the paging layer
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