realgray-stellaris-mod/common/leader_classes/RG_leader_classes.txt

103 lines
3.7 KiB
Plaintext
Raw Normal View History

# example_class = {
# name = <name_key>
# name_plural = <name_plural_key>
# description = <description_key>
#
# #all the following default to no
# can_lead_army = yes/no # Applies skill_<class_id>_army scaled by level to armies
# can_lead_navy = yes/no # Applies skill_<class_id>_navy scaled by level to fleets
# can_govern_planet = yes/no # Applies skill_<class_id>_planet_governor scaled by level to governed planet
# Applies skill_<class_id>_sector_governor scaled by level to governed sector, if governing the sector capital
# Applies skill_<class_id>_background_planet_governor scaled by level togoverned planet, if governing their homeworld
# can_be_envoy = yes/no
# can_research_tech = yes/no
# can_research_special_projects = yes/no
# can_crew_science_ship = yes/no
# can_research_anomalies = yes/no
# can_research_archaeology_site = yes/no
# can_survey = yes/no
# can_boost_cloaking_detection = yes/no
# can_explore_rifts = yes/no
# can_conduct_active_reconnaissance = yes/no
# can_govern_planet = yes/no
# can_have_traits = yes/no # defaults to yes, if no this class will not gain LEADER_ASSIGNED_MONTHLY_EXPERIENCE when assigned
# can_rule_empire = yes/no # defaults to yes
# recruitable = yes/no # defaults to yes
# max_trait_points = <num>
# leader_capacity = <num> # maximum number of leader of this type before you get maluses, 0 means no cap
# replaces_old_class = "old_class" # used for backwards compatibility. When "old_class" appears in an old save, it is converted to this class at loading
# # can appear multiple times
#
# resources = { #upkeep
# category = leader_scientists/etc
# cost = {
# ...
# }
# }
#
# ai_weight = { # used to determine which type of leader the AI prefers (frex: commanders for warlike leaders, and governor for pacifists)
# base = <num>
# modifier = {}
# }
#
# ai_location_weight = { # used to evaluate a specific leader for an assignment to a specific location (right now only used for fleet),
# # scope is the leader, from is the leader location (can be a planet, a fleet, an army etc)
# # if the score is 0 or less, the leader will not be assigned to that location
# base = <num>
# modifier = {}
# }
#
# minimum_ai_target = <num>
#
# leader_background_job_weight = {
# job_name = <weight>
# # etc
# }
# }
#
# icon = 1 # 1-based index in the icon file. might be replaced by an icon name later
#
# paragon_background_selector = <name of an asset_selector>, used to display a background behind paragon portraits
#
#
# How the AI assigns leaders now:
#
# Step 1: Sort all possible location using the NDefines::NAI::LOCATION_WEIGHT_* values (all of them are multipliers except the galactic community which is a flat value)
# Step 2: Sort all available leaders by skill
# Step 3: for each leader in order, calculate a location weight based on the ai_location_weight of their class
# Step 4: Assign the highest leader/location pair based on the weight
# Step 5: if no leader was assigned, see if hiring a leader is possible repeating the same steps
rg_nanite_leader = {
name = rg_nanite_leader
name_plural = rg_nanite_leader_plural
description = rg_nanite_leader_description
can_lead_army = yes
can_lead_navy = yes
can_govern_planet = yes
can_be_envoy = yes
can_research_tech = yes
can_research_special_projects = yes
can_crew_science_ship = yes
can_research_anomalies = yes
can_research_archaeology_site = yes
can_survey = yes
can_boost_cloaking_detection = yes
can_explore_rifts = yes
can_conduct_active_reconnaissance = yes
can_govern_planet = yes
can_have_traits = yes
can_rule_empire = yes
recruitable = no
max_trait_points = 3
leader_capacity = 3
ai_weight = {
modifier = {
factor = 0
}
}
icon = 4
paragon_background_selector = "paragon_background_selector"
}