MechInterp Glossary and Constraints

A read-only reference skill providing domain knowledge for mechanistic interpretability research on SplatNLP's SAE features.

Purpose

This skill provides the domain-specific knowledge needed to design valid experiments:

• Ability token families and their AP rungs
• Main-only vs stackable abilities
• Constraints that experiments must respect
• Common pitfalls to avoid

When to Use

Invoke this skill when you need to:

• Look up ability family codes (SCU, ISS, SSU, etc.)
• Understand AP rung meanings
• Check constraint definitions
• Verify valid token combinations

Quick Reference

Ability Family Short Codes

Code	Full Name	Stackable
SCU	special_charge_up	Yes
SPU	special_power_up	Yes
SS	special_saver	Yes
ISS	ink_saver_sub	Yes
ISM	ink_saver_main	Yes
SSU	swim_speed_up	Yes
RSU	run_speed_up	Yes
IRU	ink_recovery_up	Yes
QR	quick_respawn	Yes
QSJ	quick_super_jump	Yes
IA	intensify_action	Yes
SubPU	sub_power_up	Yes
SRU	sub_resistance_up	Yes
INKR	ink_resistance_up	Yes

Main-Only Abilities (Fixed 10 AP) — BINARY

Ability	Gear Slot
comeback	head
last_ditch_effort	head
opening_gambit	head
tenacity	head
ability_doubler	clothes
haunt	clothes
ninja_squid	clothes
respawn_punisher	clothes
thermal_ink	clothes
drop_roller	shoes
object_shredder	shoes
stealth_jump	shoes

⚠️ IMPORTANT FOR EXPERIMENTS: These abilities are binary (present or absent, no scaling). In 1D sweeps, they will always show delta = 0 because there's no AP variation to test. This does NOT mean they don't affect the feature.

⚠️ TOKEN FORMAT: Binary abilities appear as just the ability name (e.g.,

comeback

,

stealth_jump

) WITHOUT an AP suffix. They do NOT appear as

comeback_10

or

stealth_jump_10

. The

parse_token()

function returns

(name, None)

for these tokens, not

(name, 10)

.

To evaluate binary abilities:

1. Check their PageRank score (correlation with high activation)
2. Check presence rate enrichment in high-activation examples (>1.5x = characteristic)
3. Check mean activation WITH vs WITHOUT the token (delta > 0.03 = meaningful)
4. Run manual 2D analysis at each scaling ability level to see conditional effects
5. Test combinations of binary abilities together (they may have stronger effects as a group)

Standard AP Rungs

AP	Typical Source
3	1 sub slot
6	2 sub slots
12	4 subs OR 1 main
21	1 main + 3-4 subs
29	1 main + 6 subs
35	2 mains + 5 subs
41	2 mains + 7 subs
45	3 mains + 5 subs
48	3 mains + 6 subs
51	3 mains + 7 subs
54	3 mains + 8 subs
57	3 mains + 9 subs (MAX)

Constraints

one_rung_per_family (HARD)

Only one AP rung per ability family can appear in a build.

Invalid:

[swim_speed_up_21, swim_speed_up_12]

- same family, different rungs Valid:

[swim_speed_up_21, special_charge_up_12]

- different families

Rationale: AP rungs represent cumulative investment. You can't have both 21 AP and 12 AP in the same ability simultaneously.

no_weapon_gating_if_relu_floor (SOFT)

Skip weapon-specific experiments when base activation is near zero.

When base activation is at the ReLU floor (~0), activation changes become quantized and unreliable. Check

diagnostics.relu_floor_detected

before trusting weapon gating results.

valid_gear_combinations (HARD)

Main-only abilities can only appear on their designated gear slot.

Invalid: ninja_squid on headgear (it's clothes-only) Valid: ninja_squid on clothes

max_ap_budget (SOFT)

Total AP should not exceed 57 (3 mains + 9 subs).

Builds exceeding this are physically impossible in-game.

Common Pitfalls

1. Multi-rung conflicts: When sweeping family levels, ensure base contexts don't already contain the family being swept.

2. ReLU floor quantization: Low base activations cause delta measurements to be unreliable. Check for

   relu_floor_detected: true

   in diagnostics.

3. OOD token combinations: Very rare ability combinations may produce unreliable activations. Prefer combinations that appear in training data.

4. Weapon bias: Some features respond to weapon kit properties (sub/special type) rather than abilities. Control for this in experiments.

Programmatic Access

from splatnlp.mechinterp.schemas.glossary import (
    TOKEN_FAMILIES,
    DOMAIN_CONSTRAINTS,
    STANDARD_RUNGS,
    get_family_for_token,
    parse_token,
    validate_build_tokens,
    get_glossary_text,
)

# Get family for a token
family = get_family_for_token("swim_speed_up_21")
print(family.short_code)  # "SSU"

# Parse token into family and AP
name, ap = parse_token("special_charge_up_57")
# ("special_charge_up", 57)

# Validate a build
violations = validate_build_tokens(["ssu_21", "ssu_12"])
# ["Constraint 'one_rung_per_family' violated: ..."]

# Get full glossary text
text = get_glossary_text()

See Also

• mechinterp-state: Manage research hypotheses and evidence
• mechinterp-next-step-planner: Propose experiments respecting constraints
• mechinterp-runner: Execute experiments with constraint enforcement