CommandCodeAI / CommandCodeAI/command-code
Background shell tasks return empty logs; provider errors (too_many_images, timeouts) and subagent failures stall long coding sessions
Nadie ha tomado este issue todavía.
- Lenguaje dominante
- Sin datos de lenguaje
- Estrellas
- 4k
- Forks
- 350
- Métricas de merge de PR
- Sin PR fusionados en 30 d
Descripción
Long coding session crippled by tooling failures: empty background-task output, provider errors, lost subagent reports
Environment
- Windows 11, Command Code CLI (npm, v1.39.x line at the time)
- Large Android/Gradle project; long-running builds (1–5 min per gradle invocation)
- One long single-session refactor task (~15 files edited + verification builds + CI screenshot step)
Summary
A large but well-scoped coding task stretched for hours almost entirely because of harness/infra failures, not task complexity. Four classes of failure, each reproducible within the session:
1. Background shell commands return empty output logs (most damaging)
shell_commandwithrun_in_background=truerunninggradlew ... > file.log 2>&1or piped through| powershell ...produced 0-byte output logs for 20–60+ minutes while gradle had actually failed in 40 seconds.- Exit status was never surfaced; the log stayed empty; the only way to learn the real failure was to manually read
~/.gradle/daemon/9.5.0/daemon-*.out.log(the daemon's own log containede: file:///...kt:NN Unresolved reference...compile errors all along). - Piping task output through PowerShell (
| powershell -Command "$input | Select-Object -Last N") also silently lost everything. - Cost: this failure mode alone consumed the majority of the session, with multiple redundant 5–10-minute polling loops staring at empty files.
- Expected: background tasks should surface real exit codes/stderr (or at minimum, the streamed log should contain the process's output as it appears).
2. Repeated mid-session provider errors, each requiring a manual "continue"
Error: 200 Failed to process successful responseError: 500 Cannot connect to API: Connect Timeout Error (172.65.90.20-23:443)Error: 400 Invalid_request_error ... [too_many_images] GLM requests accept at most 8 inline PNG/JPEG/WEBP/GIF ...— a session that reviews screenshots (dev workflow!) becomes unsendable until the user manually compacts. The model can't fix this itself.
3. Subagent runs errored and lost their reports
- One
generalsubagent returned[sub-agent stopped early: the run errored]after 20 minutes, mid-task (had made real edits already). - A separate audit subagent died entirely with its report lost; had to be relaunched from scratch.
- Expected: partial output preserved on subagent error, or automatic retry.
4. Tool-schema friction
search_toolsrepeatedly returnedtodo_writeschema, but calling it kept failing/looping for several turns before it finally worked.
Trace IDs (from the error banners in one session)
- 6b481a97ce2ad552cb4802dc72d0b0ef
- 39a179d53c81ee36fea47ff7f116d066
- 52c2bcc5f22d1a3815bb7b6a4ce81356
- ca6c03357b892c7ca6e9042e6ecb6367
- 2cc56255ce5d8e9aab41e69325ec4e81
Ask
- Surface real exit status + stderr of background and piped shell tasks; don't let empty logs masquerade as "still running."
- Handle the image budget proactively (auto-compact or drop stale images before the provider hard-fails the whole conversation).
- Preserve subagent partial reports when a run errors.
Guía de contribución
No hay ninguna guía de contribución indexada para este repositorio
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
Línea de trabajo
Empieza por los puntos de entrada de la CLI para shell_command con run_in_background=true y reproduce los casos de Gradle y PowerShell, comparando la salida capturada con el registro del daemon y el estado de salida. Después, sigue los errores de límite de imágenes del proveedor y el manejo de errores de los subagentes, usando los trace IDs indicados cuando estén disponibles. Se considera terminado cuando los fallos en segundo plano exponen el estado y stderr, se gestionan los límites del proveedor y los subagentes con errores conservan los informes parciales.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- ai-infra-agents, cli
- Área
- ai, cli, tooling
- Tipo de issue
- Error
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Estado de actividad
- Activo
- Claridad
- Necesita aclaración
- Aptitud para principiantes
- 25/100