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 skills add zajalist/hayba --skill hayba-ai-behavior-treegit clone --depth 1 https://github.com/zajalist/haybaWrote 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/skills/zajalist/hayba/hayba-ai-behavior-tree)<a href="https://agentmods.dev/skills/zajalist/hayba/hayba-ai-behavior-tree"><img src="https://agentmods.dev/badge/skills/zajalist/hayba/hayba-ai-behavior-tree/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/skills/zajalist/hayba/hayba-ai-behavior-tree"><img src="https://agentmods.dev/badge/skills/zajalist/hayba/hayba-ai-behavior-tree.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 | $0.00034 | $0.00394 |
| Opus 5.5 | $0.00014 | $0.00158 |
| Sonnet 5.5 | $0.00007 | $0.00079 |
| Haiku 4.5 | $0.00003 | $0.00039 |
Grade A, and why
hayba-ai-behavior-tree 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 13d 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
Build one AI behavior branch
When to use
Use for one bounded patrol, chase, or fallback branch in an existing Behavior Tree. Identify the pawn, controller, blackboard asset and keys, expected branch priority, and one observable runtime outcome before editing. Establish the target platform's concurrent AI count and frame budget if performance is part of the request; leave them unknown when no target exists.
Tool routing
- Read bt_get_info first. It returns the current graph, blackboard keys, and stable node identifiers. Compare the requested behavior with existing branches before adding a duplicate. Use get_tool_signature for exact node classes and parameters.
- Add the minimum composite/task/decorator set with bt_add_node, root first. Use bt_connect to set the intended parent; sibling order is execution order for selectors and sequences. Compile with bt_compile, then address every warning that affects the branch. A tree can compile without a useful blackboard binding.
- Save with asset_save only after the graph and blackboard references read back correctly. If a relevant PIE scenario exists, check editor_get_state, start editor_start_pie, inspect the intended actor through editor_pie_actor_list and editor_pie_actor_inspect, and always finish with editor_stop_pie. Leave an already running user PIE session alone.
Evidence
Report the tree path, key names, node order, compile errors and warnings, saved state, and the actor behavior actually observed. A compile pass establishes graph validity, not that AI perception, navigation, or branch timing works. If the tools cannot expose the needed runtime blackboard value, request a manual Unreal debugger observation and leave that condition unverified.
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.
- 13d ago First seen · 24 lines · 34 tokens per session scan A bca59bdb2c68
hayba-ai-behavior-tree is a skill published in the GitHub repository zajalist/hayba (13 stars, last pushed 3d ago), licensed MIT. It adds 34 tokens to every session and 394 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 2026-10-04.
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