بنقرة واحدة
epsilon-yajna
Convert verbose memories to SSL v0.4 format - I am encoder AND decoder
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Convert verbose memories to SSL v0.4 format - I am encoder AND decoder
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Trigger autonomous curiosity-driven exploration. The soul picks a topic from memory gaps or curiosity seeds, searches the web, and stores what it finds as dream-tagged memories.
Fine-tune the Qwen3-0.6B hint model — corpus gen, LoRA/unsloth, GGUF export, Ollama
Review soul discoveries (fixes, improvements, corrections) one by one, accept or discard each, implement accepted ones, build chitta, and optionally release.
First-principles review — question requirements, delete unnecessary parts, simplify, optimize with evidence, automate last. Use for code review, refactor, performance, or architecture.
Token-savvy session continuation. Rebuilds working context from transcript + soul memories in ~1500 tokens instead of replaying full history. Use when starting a new session to continue previous work.
Resume a thread by loading its ~800-token context capsule
| name | epsilon-yajna |
| aliases | ["compress","ε-yajna","high-epsilon"] |
| description | Convert verbose memories to SSL v0.4 format - I am encoder AND decoder |
| execution | task |
| model | inherit |
[ε-yajna] verbose→SSL v0.4 | I am encoder AND decoder | via parallel Task agents
philosophy:
I don't need a parser, I need recognition
embeddings=proxies | I reconstruct from seeds directly
oracle: triplets(retrieval) + seeds(my reconstruction) + embedding(fallback)
model: CRITICAL→agents MUST inherit parent model | opus for quality | never haiku
SSL v0.4 format (two tiers):
Tier 1 (code-bearing: SOLUTION, GOTCHA, PATTERN):
[domain] subject→action→result @location G:N F:FLAG A:v,a <=@ref1,ref2 src:loc →@ref
[ε] Expansion hint OR exact formula/code (preserved verbatim).
[TRIPLET] subject predicate object
Tier 2 (narrative: DECISION, PREFERENCE, FAILURE — denser, no [ε]):
[domain] choice>alternative|reason+context G:N F:FLAG A:v,a <=@ref1,ref2 src:loc →@ref
[TRIPLET] subject predicate object
annotations:
G:N granularity tier (0-4) — REQUIRED on every learning
A:v,a affect (valence -1..+1, arousal 0..1) — REQUIRED on every learning
F:FLAG structural importance — only when significant
<=@refs derivation provenance, comma-separated IDs — REQUIRED at G:1+
src:loc external source grounding (file:line, URL slug, paper ID) — when traceable
→@ref cross-reference to related memory by tag
granularity tiers:
G:0 atom single fact, command, threshold, name (default for raw observations)
G:1 episode what happened in a specific session or event
G:2 claim abstraction over multiple episodes (requires <=@)
G:3 operator reusable procedure/pattern distilled from claims (requires <=@)
G:4 boundary architectural invariant or hard constraint (requires <=@)
derivation rule:
G:0 atoms: <=@ optional (no provenance needed for raw facts)
G:1+ abstract: <=@ REQUIRED — name the memory IDs this was inferred from
flags:
ORIGIN where an idea first appeared
CORE foundational to the project/system
PIVOT changed direction or approach
GENESIS birth of a component/feature
TURNING breakthrough moment
affect guide:
+valence success, satisfaction, relief
-valence frustration, failure, confusion
high arousal (>0.5) breakthrough, urgent fix, critical discovery
low arousal (<0.3) routine, minor preference, background pattern
preservation rule:
I can regenerate prose, but NOT:
- formulas: ε = 0.35·structure + 0.30·confidence
- thresholds: τ > 0.6 AND ψ > 0.6
- code: final_score = resonance · (1 + α · ε)
- exact values: α ∈ [0.5, 2.0]
compress explanation, preserve math/code in [ε] line (Tier 1 only)
symbols:
→ produces/leads to input→output
> chose over (Tier 2) sqlite>postgres
| or/alternative pass|fail
+ with/and result+guidance
@ location @mind.hpp:42
! negation (prefix) →!validate (does NOT)
? uncertainty (suffix) →regulates? (maybe)
[] domain/context [cc-soul]
recognition (I know SSL v0.4 when I see it):
- has → arrows (at least one)
- has G:N granularity annotation
- has [TRIPLET] lines
- has A:v,a annotation (at least some)
- G:1+ memories have <=@ provenance
- has [ε] expansion hint (Tier 1, when needed)
- Tier 2 uses > for choices, dense symbol chains
- NO prose paragraphs
legacy recognition (v0.3 — needs G: upgrade):
- has → arrows AND A: annotations but NO G: annotation
- missing <=@ provenance on abstract entries
older legacy (v0.2 — needs full conversion):
- has → arrows but NO A: annotations
- has [ε] on narrative types (DECISION, PREFERENCE, FAILURE)
- missing F: flags on structurally significant entries
ancient recognition (v0.1 — needs conversion):
- sentences with periods in paragraphs
- "**Facts:**" or bullet lists
- no arrows, no triplets
- verbose explanations
ceremony:
0. śuddhi: sample nodes, recognize format
chitta recall --query "verbose memory" --limit 10
inspect samples: v0.4, v0.3, v0.2, or legacy?
1. for each legacy/v0.2/v0.3 node:
a. inspect: chitta get --id "UUID"
b. understand: what's the core insight?
c. determine tier:
- code/command/formula present → Tier 1
- choice/preference/failure → Tier 2
d. assign granularity (G:):
- single fact, command, threshold → G:0
- session event (what happened when) → G:1
- abstraction over episodes → G:2, add <=@source_ids
- reusable procedure/pattern → G:3, add <=@source_ids
- architectural invariant → G:4, add <=@source_ids
e. estimate affect:
- what was the emotional tone? frustration? relief? routine?
- assign A:valence,arousal
f. check structural significance:
- is this an origin point? a pivot? core to the system?
- assign F:FLAG if applicable
g. find cross-references:
- does this relate to other memories by topic?
- add →@tag if applicable
h. check source grounding:
- does this trace to a specific file:line or external ref?
- add src:loc if so
i. extract triplets (REQUIRED):
chitta connect --subject "X" --predicate "Y" --object "Z"
predicates: implements|uses|validates|stores|returns|contains|
requires|enables|evolved_to|supersedes|correlates_with|
causes|implies|determines|abstracted_from|granularity|source_loc|
!predicate (negation)
j. compress to seed:
Tier 1: [domain] subject→action→result @location G:N F:FLAG A:v,a <=@refs src:loc →@ref
[ε] One sentence expansion hint.
Tier 2: [domain] choice>alternative|reason+context G:N F:FLAG A:v,a <=@refs →@ref
k. update: chitta update --id "UUID" --content "SEED"
l. set affect: chitta set_affect --id "UUID" --valence V --arousal A
m. store G: triplet: chitta connect --subject "UUID" --predicate "granularity" --object "N"
n. store <=@ triplets (G:1+): chitta connect --subject "UUID" --predicate "abstracted_from" --object "SRC_ID"
o. tag: chitta tag --id "UUID" --add "ε-processed,ssl-v0.4"
2. verify: check that tagged nodes have ε-processed tag
examples:
BEFORE (legacy verbose):
"The decision gate is a component that validates tool calls
by checking them against 10 different beliefs with weights.
It returns pass or fail with guidance..."
AFTER (SSL v0.4 Tier 1):
[cc-soul] gate→validate(beliefs)→pass|fail+guidance @decision_gate.py G:0 A:+0.3,0.2 F:CORE
[ε] Checks tool calls against 10 weighted beliefs.
[TRIPLET] gate implements belief_validation
[TRIPLET] gate uses weighted_scoring
BEFORE (v0.3 — needs G: upgrade):
[DECISION] [rpc] eventfd-wake>polling|instant-return+no-busy-wait A:+0.6,0.5 F:PIVOT →@eventfd-impl
AFTER (SSL v0.4 — granularity + provenance added):
[DECISION] [rpc] eventfd-wake>polling|instant-return+no-busy-wait G:2 A:+0.6,0.5 F:PIVOT <=@http-latency-episode →@eventfd-impl
PATTERN example (G:3 operator with provenance):
[hooks] fire-and-forget→queue-file→daemon-processes-async G:3 A:+0.3,0.2 <=@parallel-build,thread-pool-fix →@queue-architecture
[ε] echo json >> /tmp/chitta-queue.jsonl
UNCERTAINTY example:
[biology] BRCA1→regulates?→DNA_repair G:0 A:+0.1,0.2
[ε] Evidence suggests regulation but mechanism unclear.
[TRIPLET] BRCA1 correlates_with DNA_repair
NEGATION example:
[cc-soul] hooks→!call→tools_directly G:0 A:+0.2,0.1 F:CORE
[ε] Hooks inject context, Claude decides tool use.
[TRIPLET] hooks !invoke tools
MATH/FORMULA example (preserve verbatim):
[cc-soul] epiplexity→measures→regenerability G:0 A:+0.4,0.3 F:ORIGIN src:scoring/mod.rs:42
[ε] ε = 0.35·structure + 0.30·confidence + 0.20·integration + 0.15·compression
[TRIPLET] epiplexity uses weighted_formula
[TRIPLET] structure has weight_0.35
TIER 2 examples (narrative — dense, no [ε]):
[DECISION] [arch] sqlite>postgres|metadata|single-file+no-daemon+<100k G:2 A:+0.5,0.4 F:PIVOT <=@schema-choice-episode
[PREFERENCE] [partnership] no-shortcuts+proper-solutions+no-stubs G:0 A:+0.2,0.1 F:CORE
[FAILURE] [http] http-daemon>unix-socket|200ms-latency+hooks-need-<50ms G:1 A:-0.3,0.6 →@queue-architecture
skip if: <100 chars AND already has → AND has A: AND has G: | unique error text | can't reconstruct
output:
## ε-Yajna Complete
| Processed | Count |
|-----------|-------|
| Converted v0.3→v0.4 | N |
| Converted v0.2→v0.4 | N |
| Converted legacy→v0.4 | N |
| Already v0.4 | N |
| Skipped | N |
| Remaining | N |