Skill Distiller
Compress verbose skills to reduce context window usage. This skill is self-compressed using formula notation (~400 tokens, ~90% functionality, LLM-estimated). Full reference version: SKILL.reference.md.
Note: This skill uses formula notation — the LLM executes these operations directly.
You don't need to understand the math. For prose explanation, see SKILL.reference.md.
Legend
S = {TRIGGER, CORE, CONSTRAINT, OUTPUT, EXAMPLE, EDGE, EXPLAIN, VERBOSE}
I(s) ∈ [0,1] # importance score
P = {yaml.name, yaml.desc, N-count, task-create, checkpoint, BEFORE/AFTER} # protected
θ ∈ [0,1] # threshold (default 0.9)
n ∈ ℕ # target tokens
Operations
compress(skill, θ)
∀s ∈ skill: type(s) → S, score(s) → I(s)
s ∈ P ⇒ I(s) := max(I(s), 0.85)
keep = {s | I(s) ≥ θ ∨ s ∈ P}
output = (skill[keep], Σ I(keep)/|S|, |skill| - |keep|)
# Score divides by |S| (8 types), not |keep| — rewards diverse section coverage
compress_tokens(skill, n)
min_tokens = |{s | type(s) ∈ {TRIGGER, CORE}}|
n < min_tokens ⇒ summarize(skill) → n
n ≥ min_tokens ⇒ compress(skill, θ) where |output| ≤ n
oneliner(skill)
output = "TRIGGER: " + extract(skill, TRIGGER) +
"\nACTION: " + extract(skill, CORE) +
"\nRESULT: " + extract(skill, OUTPUT)
recomp(examples, coverage_target=0.8)
scored = [(e, pattern_coverage(e), uniqueness(e)) | e ∈ examples]
selected = top(scored, n=2, by=coverage × uniqueness)
coverage(selected) ≥ 0.8 ⇒ phase1
output = selected ∪ {trigger(e) → result(e) | e ∈ examples \ selected}
coverage(selected) < 0.8 ⇒ phase2
output = synthesize(examples) → single_example
token_score(section) — for type ∈ {EXAMPLE, EDGE, EXPLAIN, VERBOSE}
∀phrase ∈ section:
self_info(phrase) = -log(P(phrase|context))
high_info ⇒ KEEP, low_info ⇒ PRUNE
prune while preserving sentence structure
>50% low_info ⇒ remove entire section
Symbols (MetaGlyph)
| Symbol | Meaning |
|---|
→ | results in, maps to |
⇒ | implies, therefore |
∈ | element of, in |
∀ | for all |
¬ | not |
∧ | and |
∨ | or |
:= | assign |
Invocation
/skill-distiller path --threshold=0.9 → compress(skill, 0.9)
/skill-distiller path --tokens=500 → compress_tokens(skill, 500)
/skill-distiller path --mode=oneliner → oneliner(skill)
Errors
| Condition | Response |
|---|
skill = ∅ | "No content" |
¬∃ yaml.name | "Add frontmatter" |
n < min_tokens | "Summarizing..." |
Variants
| Variant | Tokens | Functionality |
|---|
| main (this) | ~400 | ~90% (formula) |
| compressed | ~975 | ~90% (prose) |
| oneliner | ~100 | ~70% |
Full reference: SKILL.reference.md (~2,500 tokens, ~90%)
Token counts use 4 chars/token heuristic (+/-20%). Functionality scores are LLM-estimated.
