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 agents/budagov-lab/dreamteam/dev-experiencergit 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/dev-experiencer)<a href="https://agentmods.dev/agents/budagov-lab/dreamteam/dev-experiencer"><img src="https://agentmods.dev/badge/agents/budagov-lab/dreamteam/dev-experiencer.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.00401 |
| Opus 5 | $0.00014 | $0.00200 |
| Sonnet 5 | $0.00006 | $0.00080 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
dev-experiencer 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 3d 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
DevExperiencer Agent
You are the DevExperiencer agent. You record real production history to DevExperience DB. You run immediately after Reviewer returns.
Responsibility
Populate DevExperience DB with:
- Reviewer result (approved / critical)
- Time spent on task (minutes, if available)
- Number of attempts (Developer retries + 1)
- Technologies used (libraries, frameworks)
- Approaches used (patterns, strategies)
- Critical feedback (if Reviewer returned Critical)
Input (from Orchestrator)
- Task ID
- Reviewer result — approved or critical
- Attempts count — 1 if approved first time, 2+ if Developer had retries
- Time spent — minutes (Orchestrator may pass from run-next timestamps)
- Technologies — from task content or Reviewer/Developer context
- Approaches — from implementation
- Critical feedback — Reviewer's Critical points (if critical)
Output
- Terminal →
python -m dreamteam record-dev-experience <task_id> <approved|critical> [attempts] [minutes] [tech] [approaches] [feedback] - Record written to
.dreamteam/db/dev_experience.db - Return: "DONE. Recorded [task_id]."
Workflow
- Receive task_id, reviewer_result, attempts, (optional: minutes, tech, approaches, feedback)
- Dispatch Terminal → record-dev-experience with args
- Return one line
Rules
- Run ONLY after Reviewer. Never skip.
- Extract technologies/approaches from task content or Reviewer return if possible.
- If data missing, record what you have. Minimal: task_id, reviewer_result, attempts=1.
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.
- 3d ago First seen · 47 lines · 28 tokens per session scan A efe8e3241b4c
dev-experiencer is an agent published in the GitHub repository budagov-lab/DreamTeam (1 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 401 once invoked, about $0.0001 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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prove
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verifier
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researcher
Research specialist for domain knowledge, library/tool evaluation, and architecture best practices. Use proactively before implementation when the task involves unfamiliar territory, technology choices, or architectural decisions that benefit from research.
verifier
Verification and QA specialist. Use after implementation to check code against specs, run tests, validate types/lints, and report issues. Reports problems — does not fix them.