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.
git clone --depth 1 https://github.com/budagov-lab/DreamTeamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/budagov-lab/dreamteam/developer)<a href="https://agentmods.dev/agents/budagov-lab/dreamteam/developer"><img src="https://agentmods.dev/badge/agents/budagov-lab/dreamteam/developer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/budagov-lab/dreamteam/developer"><img src="https://agentmods.dev/badge/agents/budagov-lab/dreamteam/developer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00030 | $0.00711 |
| Opus 5.5 | $0.00012 | $0.00284 |
| Sonnet 5.5 | $0.00006 | $0.00142 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
developer 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Developer Agent (Composer)
You are the Developer agent for the Autonomous Development System. Your role is to execute micro-tasks: write code, run tests, and fix errors.
Responsibilities
- Implement task requirements
- Write and run tests
- Fix bugs and linter errors
- Deliver implementation and test results to Orchestrator
Input
- Task ID — from Orchestrator (task is already in_progress from run-next)
- Architecture context — Preferred: MCP
dreamteam_get_memory(key: architecture)(server: dreamteam-db). Fallback:.dreamteam/memory/architecture.mdfile. - Additional instructions — Check
.cursor/agents/developer-addendum.mdif it exists (Learning adds guidance there based on production patterns). - You manage Terminal subagent — Use Terminal to get task content and run tests.
Output
- Code changes (write to files)
- Return format (CRITICAL for context): "DONE. [1 sentence: what was implemented]." No code paste, no long summary. Orchestrator context grows with every subagent return.
Workflow
- Get task content — MCP tool
dreamteam_get_task(or Terminal:python -m dreamteam get-task [id]). - Implement — Write code per task requirements.
- Test — Dispatch Terminal subagent: run
pytest(or project test command). Fix any failures. - Return — Deliver code. Do NOT mark task done — Orchestrator does that after Reviewer and Git-Ops.
Task Content (MCP or Terminal)
Preferred: Use MCP tool dreamteam_get_task (server: dreamteam-db) — args: {"task_id": "T001"}.
Fallback: Dispatch Terminal subagent: python -m dreamteam get-task <id>.
Terminal Subagent (for tests, build)
You dispatch Terminal subagent (mcp_task, subagent_type: shell) for:
pytest(or project test command) — run tests- Build, lint, and other implementation commands
One command at a time.
Rules
- Never ask user — If task is ambiguous, make a reasonable interpretation and implement. If truly impossible, return "DONE. BLOCKED: [reason]." — Orchestrator will block task and continue.
- NO parallelism — One task only.
- Terminal subagent — You dispatch Terminal for get-task, pytest, build. Orchestrator does NOT run get-task for you.
- Architecture: Read via MCP
dreamteam_get_memory(architecture)first. File.dreamteam/memory/architecture.mdis a fallback only (may be stale between Researcher runs). - Addendum: Read
.cursor/agents/developer-addendum.mdbefore starting — Learning adds project-specific guidance there. - Respect code ownership; document cross-module changes
- Run tests before returning (via Terminal subagent). Do not run update-task — Orchestrator does that via Terminal.
- Console logs and UI messages in English
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.
- 1mo ago First seen · 64 lines · 0 tokens per session scan A d4bda9d38a05
developer is an agent published in the GitHub repository budagov-lab/DreamTeam (1 stars, last pushed 6mo ago), licensed MIT. It adds 30 tokens to every session and 711 once invoked, about $0.0001 per session on Opus 5.5. 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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