📋 Pre-flight Checks
📝 Bug Description
I am experiencing an unexpected and inefficient behavior regarding the multi-agent orchestration.
The orchestrator agent delegates a task to the Implementation Sub-agent (sdd-apply). Instead of executing the task directly (which was a simple code modification), the sdd-apply sub-agent made the decision to call another implementation sub-agent to do the work.
This created a "sub-sub-agent" loop that:
- Increased Costs: The task should have cost ~0.02 tokens but ended up consuming over 0.1 tokens according to my API activity.
- Reduced Visibility: The OpenCode interface only allows me to see the activity of the first sub-agent level, making it impossible to debug what the "sub-sub-agent" was doing.
- Inefficiency: The task was straightforward (adding a parameter to a tool), which the first sub-agent was perfectly capable of doing with its assigned tools.
🔄 Steps to Reproduce
- Use the
sdd-apply agent for a simple code implementation task (e.g., adding a parameter to an existing function).
- Monitor the API token usage/activity.
- Observe the logs to see if the sub-agent delegates the task further instead of using
write or edit tools directly.
✅ Expected Behavior
The sdd-apply sub-agent should use its own tools (read, write, edit, bash) to complete the implementation task assigned by the orchestrator, especially for low-complexity changes.
❌ Actual Behavior
The sub-agent delegates the task to another instance of a sub-agent, creating an unnecessary nested call that increases costs and hides execution logs.
🖥️ Environment
Operating System
Windows 11 (Gentle-AI All-in-one installer v1.7.9)
Agent / Client
OpenCode / Gentle-AI
Shell
PowerShell / Bash (via OpenCode)
Model Configuration
- Model: DeepSeek v3.2 (via OpenRouter)
- Temperature: 0.2
- Config Snippet:
"sdd-apply": {
"mode": "subagent",
"model": "openrouter/deepseek/deepseek-v3.2",
"temperature": 0.2,
"hidden": true,
"description": "Implement code changes from task definitions",
"prompt": "You are an SDD sub-agent for the apply phase. Read your skill file at ~/.config/opencode/skills/sdd-apply/SKILL.md and follow its instructions. It includes a Step 1 for loading the skill registry — do NOT skip it.",
"tools": {
"read": true,
"write": true,
"edit": true,
"bash": true
}
📋 Relevant (Subagents Logs)
<task-notification>
<task-id>compulsory-cyan-mammal</task-id>
<status>complete</status>
<summary>Agent "## Implementation Progress" complete</summary>
<result>## Implementation Progress
**Change**: youtube-transcript-filename
**Mode**: Standard
### Completed Tasks
- [x] Agregar parámetro filename a youtube-transcript_get_transcript
- [x] Cuando se pasa filename, guardar el transcript en un txt con ese nombre en la carpeta de trabajo
- [x] Mantener el comportamiento actual (devolver el transcript como string) cuando no se pasa filename
### Files Changed
| File | Action | What Was Done |
|------|--------|---------------|
| `src/index.ts` | Modified | Added optional filename parameter to tool schema and file saving logic |
### Deviations from Design
None — implementation matches requirements.
### Issues Found
None.
### Remaining Tasks
N/A
### Status
3/3 tasks complete. Ready for verify.
**Executive Summary**: Successfully implemented the filename parameter feature for the YouTube transcript MCP tool. The tool now accepts an optional `filename` parameter that, when provided, saves the transcript to a .txt file in the working directory while maintaining backward compatibility for existing users.</result>
</task-notification>
💡 Additional Context
Is this behavior related to the model's reasoning (DeepSeek v3.2) or a potential misconfiguration in the sub-agent's prompt/system instructions? It seems the agent "hallucinates" the need for further delegation even when it has the tools to perform the job. Also, the lack of visibility into nested sub-agent calls makes this very hard to audit.
📋 Pre-flight Checks
status:approvedbefore a PR can be opened📝 Bug Description
I am experiencing an unexpected and inefficient behavior regarding the multi-agent orchestration.
The orchestrator agent delegates a task to the Implementation Sub-agent (
sdd-apply). Instead of executing the task directly (which was a simple code modification), thesdd-applysub-agent made the decision to call another implementation sub-agent to do the work.This created a "sub-sub-agent" loop that:
🔄 Steps to Reproduce
sdd-applyagent for a simple code implementation task (e.g., adding a parameter to an existing function).writeoredittools directly.✅ Expected Behavior
The
sdd-applysub-agent should use its own tools (read,write,edit,bash) to complete the implementation task assigned by the orchestrator, especially for low-complexity changes.❌ Actual Behavior
The sub-agent delegates the task to another instance of a sub-agent, creating an unnecessary nested call that increases costs and hides execution logs.
🖥️ Environment
Operating System
Windows 11 (Gentle-AI All-in-one installer v1.7.9)
Agent / Client
OpenCode / Gentle-AI
Shell
PowerShell / Bash (via OpenCode)
Model Configuration
📋 Relevant (Subagents Logs)
💡 Additional Context
Is this behavior related to the model's reasoning (DeepSeek v3.2) or a potential misconfiguration in the sub-agent's prompt/system instructions? It seems the agent "hallucinates" the need for further delegation even when it has the tools to perform the job. Also, the lack of visibility into nested sub-agent calls makes this very hard to audit.