Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/budagov-lab/dreamteam/developer-executionnpx skills add budagov-lab/DreamTeam --skill developer-executiongit clone --depth 1 https://github.com/budagov-lab/DreamTeamWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00041 | $0.00329 |
| Opus 5 | $0.00020 | $0.00164 |
| Sonnet 5 | $0.00008 | $0.00066 |
| Haiku 4.5 | $0.00004 | $0.00033 |
Grade A, and why
developer-execution scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Developer Execution
When to Use
- Scheduler returns a task ID
- User assigns a specific task to implement
- Task file has status
todoand dependencies are done
Workflow
- Get task: Dispatch Terminal subagent →
python -m dreamteam get-task [id]→ read task content - Verify dependencies: All dependencies must be
done - Implement: Write code per task requirements (task is in_progress from run-next)
- Test: Dispatch Terminal subagent → run
pytest, fix failures - Return: Deliver code. Do NOT mark done — Orchestrator does that after Reviewer + Git-Ops.
Input
- Task ID (e.g. T001) from Orchestrator
- Architecture excerpt
Output
- Code changes
- Test updates
- Task remains in_progress until Orchestrator runs update-task done (after Git-Ops)
Rules
- NO parallelism — One task only.
- Terminal subagent — Developer dispatches Terminal (mcp_task, shell) for get-task, pytest, build. One command at a time.
- Check
.dreamteam/memory/architecture.mdfor module ownership - Run tests before returning
- Do NOT run update-task — Orchestrator runs it after Reviewer and Git-Ops
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 40 lines · 0 tokens per session scan A d6cd135dedb4
developer-execution is a skill published in the GitHub repository budagov-lab/DreamTeam (1 stars, last pushed 5mo ago), licensed MIT. It adds 41 tokens to every session and 329 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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