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buffbuff 搜索

Agent Skill

buff 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

269

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37

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:buff(buff 搜索)
来源仓库:https://github.com/simhacker/moollm
仓库路径:skills/buff
安装命令:
npx skills add https://github.com/simhacker/moollm --skill buff
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/simhacker/moollm --skill buff

简介

用于查找、检索和筛选相关信息,支持基于关键词或任务场景快速定位候选结果。

  • 适合在需要从多源数据中获取模式识别和实现参考时使用。
  • 可通过 WebFetch 获取 Charm 生态的示例 README 和源代码。
  • 安装前建议确认权限范围和维护状态,避免触发不必要的联网或文件操作。
  • 适用于 Codex、Claude、Cursor、Gemini CLI 等宿主环境。

SKILL.md

Buff

*"All effects are buffs. Some are just shitty."*

Buffs modify stats, abilities, or behavior. They have durations, can stack, and come from various sources. Curses are just negative buffs — no separate system.

Characters Only

Buffs only target characters. This is a design constraint, not a limitation.

  • Single closure signature: (world, subject, verb, object)
  • subject is always a character — no type checking needed
  • Rooms that need buffs get a "room spirit" character
# Room needs to be "haunted"? Create its spirit.
character:
  id: dark-cave-spirit
  name: "Spirit of the Dark Cave"
  location: room/dark-cave
  buffs:
    - ref: buff/haunted

Structure

buff:
  name: "Caffeinated"
  source: "Espresso"
  effect: { energy: +2, focus: +1 }
  duration: 5  # simulation turns
  stacks: false
FieldPurpose
nameDisplay name
sourceWhat granted this buff
effectStat mods OR semantic prompt
durationHow long it lasts
stacksCan multiple instances exist?
max_stacksIf stacking, limit
decayHow it ends (time, action, condition)

Buff Types

Numeric

Traditional stat modifiers:

buff:
  name: "Caffeinated"
  effect: { energy: +2, focus: +1 }
  duration: 5

Semantic

Arbitrary effect prompts interpreted by the LLM — not predefined stats, just vibes:

  • "feeling lucky"
  • "cats seem to like you today"
  • "slightly cursed"
  • "radiating calm energy"
  • "shadows feel watchful"

How it works:

Buff: "cats seem to like you today"
Action: PAT TERPIE
LLM: Gives bonus, narrates extra warmth

Mixed

Combine numeric and semantic:

buff:
  name: "Terpie's Blessing"
  effect:
    calm: +2
    vibe: "cats trust you more"
  duration: "a while"

Standard Properties Buffs Affect

Player/NPC Stats (Sims-Style Needs)

# Numeric needs — decay over time, restored by actions
needs:
  hunger: 80      # 0=starving, 100=full
  energy: 65      # 0=exhausted, 100=rested
  social: 45      # 0=lonely, 100=connected
  hygiene: 90     # 0=filthy, 100=clean
  bladder: 30     # 0=desperate, 100=empty
  fun: 55         # 0=bored, 100=entertained
  comfort: 70     # 0=miserable, 100=cozy

Mind-Mirror Stats (Cognitive/Emotional)

# Mental state — affects decision-making and narration
mind:
  focus: 75       # Concentration (0-100)
  mood: 20        # Emotional valence (-100 to +100)
  stress: 35      # Anxiety level (0-100)
  creativity: 60  # Creative capacity (0-100)
  confidence: 50  # Self-assurance (0-100)
  patience: 40    # Frustration tolerance (0-100)
  curiosity: 80   # Exploration drive (0-100)

Room Spirit Stats

Room spirits are characters whose stats affect the room they haunt:

character:
  id: forge-spirit
  name: "Spirit of the Forge"
  location: room/blacksmith-forge

  # These stats affect everyone in the room
  production_speed: 120   # +20% crafting speed
  error_rate: 8           # 8% chance of mistakes
  mood_influence: +5      # Slight pride boost
  comfort_bonus: -10      # Hot and uncomfortable
  discovery_chance: 15    # Sometimes find rare materials
  danger_level: 25        # Burns, sparks, accidents

  buffs:
    - id: master-craftsman-blessing
      source: "Pleased the forge spirit"
      effect: { production_speed: +30, error_rate: -5 }
      duration: "until you leave"
Spirit StatWhat It DoesExample Buff Effect
production_speedWork/craft rateBlessing: +30% faster
error_rateMistake probabilityCurse: +20% more errors
mood_influenceMood granted to visitorsHaunting: -15 mood
comfort_bonusComfort modifierCozy: +20 comfort
discovery_chanceFinding hidden thingsMysterious: +25%
danger_levelHazard intensityCursed: traps more deadly

Sources

SourceExample
InteractionsPetting a cat grants joy
ConsumablesCoffee grants energy
LocationsBeing in pub grants comfort
ItemsLit lamp grants grue immunity
RelationshipsHigh friendship grants trust
PersonasWearing persona grants themed buffs

Lifecycle Hooks

Three hooks control buff behavior, written as natural language and compiled to JS:

Hook→ Compiles ToPurpose
startstart_jsRuns when buff activates
simulatesimulate_jsRuns each tick while active
is_finishedis_finished_jsReturns true → buff ends

Example: Poison Buff

buff:
  id: poison
  name: "Poisoned"
  tags: [curse, damage-over-time, dispellable]

  # Natural language prompts (author writes these)
  start: "Mark character as poisoned, turn them slightly green"
  simulate: "Reduce HP by 1, chance of groaning sound"
  is_finished: "Return true after 5 ticks OR if HP drops below 10"

  # Compiled by buff compiler (generated)
  start_js: |
    subject.poisoned = true;
    subject.tint = 'green';
  simulate_js: |
    subject.hp -= 1;
    if (Math.random() < 0.3) world.emit('*groan*');
  is_finished_js: |
    return subject.poisonTicks >= 5 || subject.hp < 10;

Closure Signature

All compiled hooks use the same signature:

(world, subject, verb, object) => { ... }
  • world — shared game state (never null)
  • subject — the character with the buff (never null for buffs)
  • verb — context-dependent (may be null)
  • object — context-dependent (may be null)

Body-only in YAML: Write just the code body, engine wraps it.

Buff Interactions

Buffs can look up and modify other buffs by tag:

InteractionEffectExample
cancelsRemove buffs with these tagsAntidote cancels [poison]
boostsMultiply/extend buffs with tagsFire spell boosts [fire] x2
replacesRemove old, add thisDrunk replaces [tipsy]
merges_withCombine into new buffRage + Focus → Battle Trance
blocked_byCan't apply if these existPoison blocked by [immunity-poison]
countersWeaken/shorten these buffsOJ counters [hangover]
countered_byThese weaken/shorten thisCouch-lock countered by [citrus]

Cancel Example

buff:
  id: cleanse
  name: "Cleanse"
  tags: [holy, dispel]
  cancels: [curse, poison, disease]  # Remove all matching
  start: "Holy light purges dark afflictions"

Boost Example

buff:
  id: fire-attunement
  name: "Fire Attunement"
  boosts:
    tags: [fire]
    multiplier: 2.0
    extend_duration: 5
  start: "Fire spells burn twice as hot"

Merge Example

buff:
  id: rage
  name: "Rage"
  tags: [combat, aggression]
  merges_with:
    tags: [focus, discipline]
    result: battle-trance  # Creates new combined buff

buff:
  id: battle-trance
  name: "Battle Trance"
  tags: [combat, legendary]
  effect: { damage: +50%, focus: +30, pain_immunity: true }
  start: "Fury and focus unite — you become a weapon"

Blocked By Example

buff:
  id: poison
  name: "Poisoned"
  tags: [poison, damage-over-time]
  blocked_by: [immunity-poison, divine-protection]
  # Won't apply if target has these tags

Weight Trees (ML-Style Mixtures)

Buffs can form hierarchical weighted mixtures, like neural network layers:

Blend → Strains → Terpenes → Effects
  ↓        ↓          ↓          ↓
weights  weights    weights    final
  ↑        ↑          ↑          ↑
 BUFFS   BUFFS      BUFFS     BUFFS   ← Each stage can be modified by buffs!

Meta-buffs can modify the weight tree itself:

BuffAffectsExample
toleranceStrain weightsRegular use → diminishing returns
sensitivityTerpene weightsFirst time → effects amplified
synergy-boostEffect weightsEntourage → all effects +20%
citrus-claritySpecific terpenesLimonene effects doubled
indica-affinityStrain categoryIndica strains hit harder

Tolerance Relationships

Tolerances use the character relationship map — same system as NPC friendships:

character:
  id: player
  name: "Don"

  # Relationships include people AND substances
  # Terpenes are unidirectional — they don't have feelings back
  relationships:
    # NPCs (bidirectional)
    bob: { trust: 45, friendship: 60 }
    alice: { trust: 80, friendship: 75 }

    # Terpene tolerances (unidirectional — no reciprocal)
    terpene/myrcene: { tolerance: 45 }      # Couch-lock less effective
    terpene/limonene: { tolerance: 12 }     # Citrus hits hard
    terpene/pinene: { tolerance: 30 }
    terpene/linalool: { tolerance: 5 }      # Lavender knocks you out
    terpene/caryophyllene: { tolerance: 60 } # Need more for pain relief
    terpene/humulene: { tolerance: 20 }
    terpene/terpinolene: { tolerance: 8 }   # Full creative boost
    terpene/ocimene: { tolerance: 3 }       # Maximum effect

Key difference from NPC relationships:

AspectNPC RelationshipTerpene Relationship
DirectionBidirectionalUnidirectional
ReciprocalBob likes you backMyrcene has no feelings
Tracked onBoth charactersPlayer only
DecayNeglect hurts bothTime heals tolerance

Tolerance mechanics:

ToleranceMultiplierExperience
0 (virgin)1.5x"Whoa, this is intense"
25 (light)1.2x"Nice, I feel it"
50 (moderate)1.0x"Standard effect"
75 (heavy)0.7x"Need more than usual"
100 (maxed)0.4x"Barely feel anything"

Tolerance changes:

# Each use increases tolerance
on_use:
  tolerance_gain: 2-5 points per use

# Tolerance decays over time (T-break!)
on_rest:
  tolerance_decay: 1 point per day of abstinence

# Full reset after extended break
t_break:
  duration: 2 weeks
  effect: "Reset to 50% of current tolerance"

Effective weight calculation:

def get_effective_terpene_weight(character, terpene, base_weight):
    tolerance = character.tolerances.get(terpene, 0)

    # Convert tolerance to multiplier
    if tolerance < 25:
        multiplier = 1.5 - (tolerance / 50)  # 1.5x → 1.0x
    elif tolerance < 75:
        multiplier = 1.0 - ((tolerance - 50) / 100)  # 1.0x → 0.75x
    else:
        multiplier = 0.75 - ((tolerance - 75) / 100)  # 0.75x → 0.5x

    return base_weight * multiplier

Layer 1: Terpenes → Effects

Each terpene has weighted effects:

myrcene-blessing:
  effects_weighted:
    relaxation: { value: +30, weight: 1.0 }   # Full effect
    pain_relief: { value: +20, weight: 0.8 }  # 80%
    sedation: { value: +25, weight: 0.9 }     # 90%

Layer 2: Strains → Terpenes

Each strain is a weighted mixture of terpenes:

strain-og-kush:
  terpene_profile:
    myrcene: 0.35      # 35% of profile
    limonene: 0.25     # 25%
    caryophyllene: 0.20
    linalool: 0.10
    humulene: 0.10

Layer 3: Blends → Strains

Blends mix multiple strains:

blend-wake-and-bake:
  strain_mixture:
    sour-diesel: 0.50     # Half the blend
    jack-herer: 0.30      # 30%
    pineapple-express: 0.20

Computing Final Effects

# Blend → Strain → Terpene → Effect propagation
def compute_blend_effects(blend):
    final_terpenes = {}

    # Layer 3→2: Blend weights × Strain terpene profiles
    for strain_id, strain_weight in blend.strain_mixture.items():
        strain = get_strain(strain_id)
        for terpene, terpene_weight in strain.terpene_profile.items():
            final_terpenes[terpene] += strain_weight * terpene_weight

    # Layer 2→1: Terpene amounts × Effect weights
    final_effects = {}
    for terpene, amount in final_terpenes.items():
        terpene_buff = get_terpene_buff(terpene)
        for effect, config in terpene_buff.effects_weighted.items():
            final_effects[effect] += amount * config.weight * config.value

    return final_effects

Example Calculation

Wake & Bake Blend:
├── Sour Diesel (50%)
│   ├── limonene: 0.30 × 0.50 = 0.15
│   └── pinene: 0.15 × 0.50 = 0.075
├── Jack Herer (30%)
│   ├── limonene: 0.20 × 0.30 = 0.06
│   └── pinene: 0.25 × 0.30 = 0.075
└── Pineapple Express (20%)
    ├── limonene: 0.30 × 0.20 = 0.06
    └── pinene: 0.25 × 0.20 = 0.05

Final limonene: 0.15 + 0.06 + 0.06 = 0.27
Final pinene: 0.075 + 0.075 + 0.05 = 0.20

Then: limonene × mood_boost, pinene × focus → final character effects

This is essentially a mini neural network where:

  • Weights are terpene profiles and strain mixtures
  • Activations are effect values
  • Forward pass computes final buff effects

Buff Orchestration (Simulation Loop)

The orchestrator runs buff rounds during simulation ticks:

1. Scan Phase

Orchestrator collects all active buffs across all characters:

# Orchestrator builds active-buff manifest
active_buffs:
  - character: player
    buff_ref: "skills/buff/buffs/INDEX.yml#caffeinated"
    remaining: 6
    stacks: 2

  - character: player
    buff_ref: "skills/buff/buffs/INDEX.yml#high"
    remaining: 8
    stacks: 1

  - character: bob-npc
    buff_ref: "skills/buff/buffs/INDEX.yml#drunk"
    remaining: 4
    stacks: 1

2. Event Generation

Create buff-tick events with pointers:

buff_round:
  tick: 42
  events:
    - type: buff-simulate
      character: player
      buff: caffeinated
      simulate_js: "subject.energy_effective += 20; subject.focus_effective += 15;"

    - type: buff-simulate
      character: player
      buff: high
      simulate: "Deep thoughts about random topics, food cravings"
      simulate_js: "if (Math.random() < 0.3) world.emit('*ponders existence*');"

    - type: buff-simulate
      character: bob-npc
      buff: drunk
      simulate: "Occasional slurred speech, may say embarrassing things"

3. LLM Simulation Prompt

Orchestrator instructs LLM to enumerate and simulate:

prompt: |
  BUFF ROUND — Tick 42

  Enumerate and simulate each active buff:

  1. PLAYER — Caffeinated (6 ticks remaining, 2 stacks)
     Effect: +20 energy, +15 focus per stack
     Simulate: Apply effects, note jitteriness if 2+ stacks

  2. PLAYER — High (8 ticks remaining)
     Effect: -25 stress, +20 creativity, +30 hunger
     Simulate: "Deep thoughts about random topics, food cravings"
     → Narrate any random musings or munchie urges

  3. BOB — Drunk (4 ticks remaining)
     Effect: +30 confidence, -25 focus, -30 judgement
     Simulate: "Occasional slurred speech, may say embarrassing things"
     → Decide if Bob says something regrettable this tick

  For each buff:
  - Apply stat modifications to _effective values
  - Run simulate behavior (chance-based events)
  - Check is_finished conditions
  - Decrement remaining duration
  - Remove expired buffs, trigger spawns_after

  Return updated character states and any narration.

4. Buff Lifecycle Per Tick

┌─────────────────────────────────────────────────────────────────┐
│                        BUFF TICK                                 │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  For each character:                                             │
│    For each active buff:                                         │
│                                                                  │
│      1. APPLY EFFECTS                                            │
│         stat_effective += buff.effect × buff.stacks             │
│                                                                  │
│      2. RUN SIMULATE                                             │
│         Execute simulate_js OR let LLM interpret simulate       │
│         (chance-based events, narration, random behaviors)      │
│                                                                  │
│      3. CHECK IS_FINISHED                                        │
│         If is_finished_js returns true → mark for removal       │
│         If remaining <= 0 → mark for removal                    │
│                                                                  │
│      4. DECREMENT DURATION                                       │
│         remaining -= 1                                           │
│                                                                  │
│      5. HANDLE EXPIRATION                                        │
│         If marked for removal:                                   │
│           - Remove buff from character                           │
│           - Trigger spawns_after buffs (with delay/chance)      │
│           - Emit buff-expired event                              │
│                                                                  │
│      6. HANDLE INTERACTIONS                                      │
│         Check for cancels, boosts, replaces, merges             │
│         Apply buff-on-buff effects                               │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘

5. Compiled vs Interpreted

ModeWhenHow
Compiledsimulate_js existsEngine evals cached closure directly
InterpretedOnly simulate textLLM reads prompt, narrates behavior
HybridBoth existJS runs effects, LLM narrates flavor
buff:
  id: drunk
  # LLM interprets this for narration
  simulate: "Occasional slurred speech, may say embarrassing things"
  # Engine runs this for mechanics
  simulate_js: |
    if (Math.random() < 0.2) {
      world.emit(subject.name + " slurs something incomprehensible");
    }

6. Attention Concentration (Time-Slicing)

The event-based design concentrates LLM attention on specific tasks:

┌──────────────────────────────────────────────────────────────────┐
│              LLM ATTENTION TIME-SLICING                          │
├──────────────────────────────────────────────────────────────────┤
│                                                                   │
│  Instead of: "Simulate everything at once" (diffuse attention)   │
│                                                                   │
│  We do: Series of focused micro-tasks                            │
│                                                                   │
│  ┌─────────┐   ┌─────────┐   ┌─────────┐   ┌─────────┐          │
│  │ Buff 1  │ → │ Buff 2  │ → │ Buff 3  │ → │ Buff 4  │          │
│  │ PLAYER  │   │ PLAYER  │   │ BOB     │   │ ROOM    │          │
│  │ caffein │   │ high    │   │ drunk   │   │ haunted │          │
│  └─────────┘   └─────────┘   └─────────┘   └─────────┘          │
│       ↓             ↓             ↓             ↓                │
│   [focused]    [focused]    [focused]    [focused]               │
│   attention    attention    attention    attention               │
│                                                                   │
└──────────────────────────────────────────────────────────────────┘

Why this works:

ProblemSolution
LLM loses track with many buffsOne buff at a time, clear context
Effects get confused/mergedEach buff isolated in its own slice
Hard to debugEach event is traceable, logged
Inconsistent simulationSame prompt structure every time

Iteration Pattern:

# Orchestrator feeds LLM one task at a time
iteration_1:
  focus: "PLAYER's Caffeinated buff"
  context: [player_state, buff_definition, tick_number]
  task: "Apply effects, check finish condition, narrate if needed"
  output: [updated_state, narration, events]

iteration_2:
  focus: "PLAYER's High buff"
  context: [player_state, buff_definition, tick_number]
  task: "Apply effects, chance of munchies event, narrate thoughts"
  output: [updated_state, narration, events]

# ... and so on

Benefits:

  1. Focused attention — LLM only thinks about one buff
  2. Predictable structure — Same input/output format each time
  3. Debuggable — Can trace exactly which buff caused what
  4. Parallelizable — Independent buffs can run in parallel
  5. Interruptible — Can pause/resume between iterations
  6. Cacheable — Compiled _js buffs skip LLM entirely

Speed-of-Light Compatible:

This fits the speed-of-light pattern — many focused micro-operations in a single LLM call, or batched across calls:

# Single call, multiple focused tasks
prompt: |
  Process these buff events in sequence:

  [1/4] PLAYER — Caffeinated
  → Apply: energy +40, focus +30 (2 stacks)
  → Check: is_finished? No (6 remaining)
  → Output: state changes only

  [2/4] PLAYER — High
  → Apply: stress -25, creativity +20, hunger +30
  → Simulate: "Deep thoughts" — roll for musing
  → Output: state + optional narration

  [3/4] BOB — Drunk
  → Apply: confidence +30, focus -25
  → Simulate: "Slurred speech" — roll for embarrassment
  → Output: state + optional narration

  [4/4] LIBRARY-SPIRIT — Haunted
  → Apply: error_rate +15, mood_influence -20
  → Simulate: "Poltergeist activity" — roll for book fall
  → Output: room effects + optional event

Stacking

  • Same source: Doesn't stack — refresh duration instead
  • Different sources: Stack additively up to category limit

Category Limits

terpene_effects: 3
charm_effects: 5
consumable_effects: 4
negative_effects: 3  # 3+ same negative = LEGENDARY

Synergies

Some buffs COMBINE into stronger effects:

  • Myr + Lily = "Sedation Stack"
  • Lemon + Pine = "Focus Boost"
  • All 8 kittens = "ENTOURAGE EFFECT" (legendary)

Negative Buffs (Curses)

Curses are just shitty buffs. Same structure, negative effects.

buff:
  name: "Scratched"
  source: "Failed BELLY RUB"
  effect: { hp: -1, visible_marks: true }
  duration: "Until healed"

Persistent Curses

Long-term negative buffs with lift conditions:

buff:
  name: "Curse of Darkness"
  effect: { lamp_efficiency: -25% }
  duration: conditional
  lift_condition: "Light 3 dark places"
  reward_on_lift: "LIGHT-BEARER title"

Duration Types

TypeExample
Turnsduration: 4
Conditionalduration: until you eat
While presentduration: while in pub
Permanentduration: forever
Natural languageduration: a few minutes
Probabilisticduration: 25% fade chance per turn

Natural Language Durations

We're not tracking real time — the LLM interprets and makes its best guess:

  • "forever"
  • "5 minutes"
  • "a day"
  • "until sunset"
  • "randomly 50%"
  • "a while"
  • "briefly"
  • "until you forget"

See time/ for full natural duration examples.

Decay

When LLM judges turn(s) have passed:

  1. Decrement duration on timed buffs
  2. Remove buffs that hit 0
  3. Apply new buffs from current turn

Effective Derived Values: Flags Edition

This is the effective derived values protocol for booleans.

TypeBaseModifiersEffective
Numericenergy: 5buff +2effective_energy: 7
Booleanin_darkness: falseroom.lit=false, has_lamp=falseeffective_in_darkness: true

Same pattern:

  • Numeric: base + sum(modifiers) = effective
  • Boolean: base OR any(conditions) = effective flag

Push / Pull / Latch

The LLM can handle any combination:

ModePatternExample
PullCompute on demandin_darkness derived from lamp + room state
PushSource sets flagBuff explicitly sets urgent_situation: true
LatchStays until clearedhas_visited_room_a: true persists
# PULL — derived on demand, not stored
in_darkness: (room.lit == false) AND (has_lamp == false)

# PUSH — buff explicitly sets
buff:
  sets_flags: [urgent_situation]

# LATCH — persists in state until cleared
player:
  visited_rooms: [room-a, room-b]  # grows, never shrinks

Traditional reactive systems pick one mode. The LLM does all three simultaneously — it sees the whole context and figures out which pattern applies.

Tweening and Animation

Values don't have to snap — they can interpolate over time:

TypeInstantTweened
Numericenergy: 5 → 7energy: 5 → 7 over 3 turns
Booleanlit: false → truelit: fading in over 2 turns
Positionroom-a → room-bwalking through hallway
buff:
  name: "Warming Up"
  effect: { warmth: +3 }
  tween: ease-in    # Gradual increase
  duration: 5

animation:
  entering_room:
    from: hallway
    to: pub
    frames: [approaching, at_door, stepping_in, arrived]

The LLM narrates intermediate states. "You feel yourself warming up..." not just "You are warm now."

Velocity

Any reactive variable can have a rate of change:

energy:
  value: 5
  velocity: -1      # Draining 1 per turn

trust:
  value: 45
  velocity: +3      # Building rapport

mood:
  value: "content"
  velocity: "improving"  # Semantic velocity works too
VariableValueVelocityMeaning
energy5-1Tired and getting worse
trust45+3Relationship strengthening
positionroom-anorthMoving northward
moodanxiouscalmingSettling down

The LLM reads velocity to predict and narrate: *"You're running low on energy and fading fast..."* vs *"Low energy but recovering."*

Physics Simulation

Extend to full 2D/3D cartoon physics:

thrown_ball:
  position: [5, 3]
  velocity: [2, 4]       # Moving up-right
  acceleration: [0, -1]  # Gravity pulling down

bouncing:
  elasticity: 0.8        # Loses 20% on bounce

cartoon_physics:
  hang_time: true        # Pause at apex
  squash_stretch: true   # Deform on impact
  delayed_fall: true     # Look down first, then fall

The LLM narrates physics with cartoon timing:

*The ball arcs gracefully upward... hangs for a moment at the peak... then plummets, SQUASHING flat against the floor before bouncing back slightly less enthusiastically.*

Works for:

  • Thrown objects (ball, inventory items)
  • Character movement (jumping, falling, knockback)
  • Environmental effects (swinging doors, rolling boulders)
  • Looney Tunes logic (run off cliff, pause, look down, THEN fall)
  • Temperature cooling or warming (ice cream melting, water freezing)

Commands

CommandEffect
BUFFS or STATUSList active buffs with remaining duration
EXAMINE [buff]Full details of buff source, effect, duration

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.27%
按下载量换算29

Claude

29.83%
按下载量换算26

Cursor

18.26%
按下载量换算16

Gemini CLI

9.71%
按下载量换算8

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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