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feat(preamble): T3 — jargon dedup + terse-build flag (Phase A.2 + A.3)
A.2 jargon dedup: generate-writing-style.ts replaces the inlined 80-term jargon list with a one-line pointer to scripts/jargon-list.json. The list was duplicated into every tier-2+ skill (48 of 51 skills); inlining cost was ~1.5 KB × 48 = ~70 KB across the corpus. Pointer cost is ~30 bytes per skill. Agents Read the JSON once per session on first jargon term encountered; thereafter the terms array is the canonical reference. A.3 terse build flag: --explain-level=terse compresses preamble prose at gen time. When the flag is set, writing-style collapses to a one-line terse directive and completeness-section + confusion-protocol + context-health are dropped entirely. The default build keeps the runtime-conditional behavior intact (sections still render; the model skips them when EXPLAIN_LEVEL: terse appears in the preamble echo). Terse build is opt-in for users who want shipped skills to match their runtime preference and avoid the per-session terse-mode dead prose. TemplateContext gains an optional `explainLevel: 'default' | 'terse'` field. Default builds set it to 'default'; --explain-level=terse sets 'terse'. Resolvers gate their output via `ctx?.explainLevel === 'terse'`. Measured impact (default build, post-T3): - Total corpus: 2,847 KB → 2,812 KB (saved 35 KB) - ship.md: 160 → 159 KB - plan-ceo-review.md: 128 → 127 KB - Top 10 heaviest: all slightly smaller from jargon pointer Larger compression lands in T4 (catalog trim) and T7 (atomic regen across the full Phase A pipeline). The terse build path further compresses to ~711K tokens vs default ~725K (saved ~14K tokens corpus-wide). Test plan: - bun test test/gen-skill-docs.test.ts: 389 pass (no regression) - bun test test/resolver-entry.test.ts: 6 pass - bun test test/helpers/capture-parity-baseline.test.ts: 4 pass - bun run gen:skill-docs --explain-level=terse: ship.md drops completeness + confusion-protocol + context-health sections; writing-style collapses to one-line terse directive 48 SKILL.md files updated (every tier-2+ skill picks up the jargon pointer). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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@@ -547,84 +547,7 @@ Applies to AskUserQuestion, user replies, and findings. AskUserQuestion Format i
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- User-turn override wins: if the current message asks for terse / no explanations / just the answer, skip this section.
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- Terse mode (EXPLAIN_LEVEL: terse): no glosses, no outcome-framing layer, shorter responses.
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Jargon list, gloss on first use if the term appears:
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- idempotent
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- idempotency
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- race condition
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- deadlock
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- cyclomatic complexity
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- N+1
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- N+1 query
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- backpressure
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- memoization
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- eventual consistency
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- CAP theorem
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- CORS
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- CSRF
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- XSS
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- SQL injection
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- prompt injection
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- DDoS
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- rate limit
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- throttle
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- circuit breaker
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- load balancer
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- reverse proxy
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- SSR
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- CSR
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- hydration
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- tree-shaking
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- bundle splitting
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- code splitting
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- hot reload
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- tombstone
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- soft delete
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- cascade delete
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- foreign key
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- composite index
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- covering index
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- OLTP
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- OLAP
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- sharding
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- replication lag
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- quorum
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- two-phase commit
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- saga
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- outbox pattern
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- inbox pattern
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- optimistic locking
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- pessimistic locking
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- thundering herd
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- cache stampede
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- bloom filter
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- consistent hashing
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- virtual DOM
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- reconciliation
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- closure
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- hoisting
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- tail call
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- GIL
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- zero-copy
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- mmap
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- cold start
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- warm start
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- green-blue deploy
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- canary deploy
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- feature flag
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- kill switch
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- dead letter queue
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- fan-out
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- fan-in
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- debounce
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- throttle (UI)
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- hydration mismatch
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- memory leak
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- GC pause
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- heap fragmentation
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- stack overflow
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- null pointer
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- dangling pointer
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- buffer overflow
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Curated jargon list lives at `~/.claude/skills/gstack/scripts/jargon-list.json` (80+ terms). On the first jargon term you encounter this session, Read that file once; treat the `terms` array as the canonical list. The list is repo-owned and may grow between releases.
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## Completeness Principle — Boil the Lake
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