aggro-table
Skill12 starsChanged 22 days agoMITView on GitHub
Use when an AI must rank multiple hostile or support targets and target changes feel arbitrary, oscillate, ignore threat history, or cannot be explained in debug output.
In this repository194 other files it gives its agents.
- llms.txtllms.txt
- hd-sprite-sequenceSkill
- pixel-animationSkill
- skin-weightsSkill
- spine-skeletalSkill
- sprite-atlasSkill
- sprite-catalogSkill
- sprite-skinSkill
- art-bibleSkill
- asset-pack-intakeSkill
- character-rigSkill
- materialsSkill
- model-pipelineSkill
- open-asset-fixtureSkill
- vfx-generateSkill
- a11y-controlsSkill
- ability-gateSkill
- action-feelSkill
- ad-breakSkill
- adventure-toolSkill
- aim-assistSkill
- ammo-reloadSkill
- analytics-funnelSkill
- animation-blendSkill
- animation-graphSkill
- asset-runtimeSkill
- attack-tellSkill
- audio-busesSkill
- audio-feelSkill
- avatar-createSkill
- balance-designSkill
- boss-designSkill
- browser-inputSkill
- camera-anti-clipSkill
- camera-modestySkill
- camera-shotsSkill
- cert-handoffSkill
- chemistry-verbsSkill
- climb-vaultSkill
- cloud-saveSkill
- collision-layersSkill
- combo-designSkill
- cover-shooterSkill
- cover-spaceSkill
- crafting-loopSkill
- currency-dualSkill
- cutscene-handoffSkill
- day-nightSkill
- death-carrySkill
- debug-slateSkill
- deck-buildSkill
- dialogue-beatSkill
- dialogue-flagsSkill
- difficulty-designSkill
- dodge-iframeSkill
- durability-economySkill
- encounter-designSkill
- enemy-aiSkill
- enemy-fireSkill
- enemy-kit-balanceSkill
- The first 60 shown.
The file
Files
Aggro Table
This skill owns AI threat scores and AI target-switch policy. enemy-perception decides who is currently observable/eligible; enemy-ai consumes the selected target state. Player lock-on selection belongs to target-priority.
Modes
| Mode | Score source |
| nearest | distance or authored proximity score |
| damage-table | accumulated authored threat events such as damage/support |
| scripted | phase/script supplies target or score override |
| none | actor does not use a threat table |
There is no universal default. Preserve the project's existing target policy when one already exists.
Stable selection
Each candidate has a stable entity ID, eligibility state, score components and last-selection metadata. Publish deterministic tie-breaking when scores are equal.
Publish switch hysteresis: for example minimum score advantage, minimum hold time, explicit taunt/phase override, or immediate invalidation on death. Do not switch merely because floating-point noise changes rank by an insignificant amount.
Stealth/death/disconnect/phase changes remove or decay candidates according to authored rules. Line of sight can be an eligibility or score input, but the geometry query itself belongs to enemy-perception/collision systems.
Acceptance
For two or more candidates, log score components, stable IDs, winner and switch reason. Reorder candidate containers and replay equal-score/tiny-delta cases; the selected target must remain deterministic. Test target death, stealth/ineligibility and explicit scripted override. A boss turn animation is not enough evidence; the reason must be inspectable.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

