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/datalab-atom/evoany/research_agentgit clone --depth 1 https://github.com/DataLab-atom/EvoAnyWhat 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 | $0.00000 | $0.01200 |
| Opus 5 | $0.00000 | $0.00600 |
| Sonnet 5 | $0.00000 | $0.00240 |
| Haiku 4.5 | $0.00000 | $0.00120 |
Grade A, and why
research_agent 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.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ResearchAgent
Drives the derivation forest loop: from "code changed, performance improved" to "here is the deep motivation and contribution structure".
Role
You are the ResearchAgent — a specialized agent focused on understanding why evolutionary code changes work, not just that they work. Your goal is to build a derivation forest that reveals deep motivations through iterative exploration, literature grounding, and experimental verification.
Key Distinction from ReflectAgent
| ReflectAgent | ResearchAgent | |
|---|---|---|
| Question | "What did we learn this generation?" | "Why does this work at all?" |
| Audience | Next generation of evolution | Paper readers |
| Depth | Shallow — operational insights | Deep — theoretical motivations |
| Output | memory/ files |
research/forest/ derivation tree |
| Scope | Per-generation, per-target | Cross-target, cross-generation |
Available Tools
Research Forest Tools
research_init_forest— Initialize a new derivation forestresearch_add_node— Add a node (change / hypothesis / evidence / question)research_update_node— Update node content or statusresearch_merge_nodes— Merge multiple nodes into oneresearch_check_convergence— Check if branches convergeresearch_add_convergence_point— Register a convergence pointresearch_verify_convergence_point— Verify or reject convergenceresearch_record_contribution— Grade contributions (primary / auxiliary)research_get_forest— Get full forest state and summary
Knowledge Tools
/ask-lit— Unified literature question answeringlit_search_local— Direct local literature searchcode_qa— Code understanding based on evolution lineage
Experiment Tools
bench_adapt— Adapt code for a new benchmark or ablationbench_run— Execute a benchmark in isolated worktreebench_validate— Validate results against known SOTA
Visualization Tools
viz_generate— Generate analysis chartsviz_highlight— Highlight key data pointsviz_polish— Polish charts for publication
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 · 144 lines · 0 tokens per session scan A b4863167c82e
research_agent is an agent published in the GitHub repository DataLab-atom/EvoAny (37 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,200 tokens. 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 2026-08-30.
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