chore: import upstream snapshot with attribution
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/**
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* GBrain resolver — brain-first lookup and save-to-brain for thinking skills.
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*
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* GBrain is a "mod" for gstack. When installed, coding skills become brain-aware:
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* they search the brain for context before starting and save results after finishing.
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*
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* These resolvers are suppressed on hosts that don't support brain features
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* (via suppressedResolvers in each host config). For those hosts,
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* {{GBRAIN_CONTEXT_LOAD}}, {{GBRAIN_SAVE_RESULTS}}, {{BRAIN_PREFLIGHT}},
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* {{BRAIN_CACHE_REFRESH}}, and {{BRAIN_WRITE_BACK}} all resolve to empty string.
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*
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* Compatible with GBrain >= v0.10.0 (search CLI, doctor --fast --json, entity enrichment).
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*
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* Brain-aware planning (T4 / v1.48 plan): adds three new resolvers powered by
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* the bin/gstack-brain-cache CLI and scripts/brain-cache-spec.ts. The new
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* resolvers fire only for the 5 planning skills registered in
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* SKILL_DIGEST_SUBSETS (office-hours, plan-ceo-review, plan-eng-review,
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* plan-design-review, plan-devex-review).
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*/
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import type { TemplateContext } from './types';
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import {
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SKILL_DIGEST_SUBSETS,
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SKILL_CALIBRATION_WEIGHTS,
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BRAIN_CACHE_ENTITIES,
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getSkillSubset,
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getInvalidationTargets,
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} from '../brain-cache-spec';
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// Per-skill slug + title + tag metadata for SAVE_RESULTS. The full save
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// template (heredoc body, entity-stub instructions, throttle handling,
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// backlinks) lives in docs/gbrain-write-surfaces.md §Save Template and is
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// read on-demand by the agent. Compressing the inline prose keeps the
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// token footprint at ~150 tokens per skill (down from ~500), so users with
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// gbrain installed pay a small overhead and users without it (whose hosts
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// have GBRAIN_SAVE_RESULTS suppressed at gen-time) pay nothing.
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interface SkillSaveMeta {
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slugPrefix: string;
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title: string;
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tag: string;
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}
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const skillSaveMap: Record<string, SkillSaveMeta> = {
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'office-hours': { slugPrefix: 'office-hours', title: 'Office Hours', tag: 'design-doc' },
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'investigate': { slugPrefix: 'investigations', title: 'Investigation', tag: 'investigation' },
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'plan-ceo-review': { slugPrefix: 'ceo-plans', title: 'CEO Plan', tag: 'ceo-plan' },
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'plan-eng-review': { slugPrefix: 'eng-reviews', title: 'Eng Review', tag: 'eng-review' },
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'plan-design-review': { slugPrefix: 'design-reviews', title: 'Design Review', tag: 'design-review' },
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'plan-devex-review': { slugPrefix: 'devex-reviews', title: 'Devex Review', tag: 'devex-review' },
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'retro': { slugPrefix: 'retros', title: 'Retro', tag: 'retro' },
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'ship': { slugPrefix: 'releases', title: 'Release', tag: 'release' },
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'cso': { slugPrefix: 'security-audits', title: 'Security Audit', tag: 'security-audit' },
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'design-consultation': { slugPrefix: 'design-systems', title: 'Design System', tag: 'design-system' },
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};
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export function generateGBrainContextLoad(ctx: TemplateContext): string {
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let base = `## Brain Context Load
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**Skip this entire section if \`gbrain\` is not on PATH.**
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Extract 2-4 keywords from the user's request. Search the brain:
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\`gbrain search "<keywords>"\`. Read the top 3 results with
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\`gbrain get_page "<slug>"\`. Use that context to inform your analysis.
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If \`gbrain search\` returns no results or any non-zero exit, proceed
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without brain context. Full search/read protocol + examples:
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see \`docs/gbrain-write-surfaces.md\` §Context Load.`;
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if (ctx.skillName === 'investigate') {
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base += `\n\nFor structured-data extraction requests ("track this", "extract from emails", "build a tracker"), route to GBrain's data-research skill instead: \`gbrain call data-research\`.`;
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}
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return base;
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}
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export function generateGBrainSaveResults(ctx: TemplateContext): string {
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// gbrain v0.18+ uses `gbrain put <slug>` (NOT the deprecated `put_page`
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// MCP op). Compressed in v1.50.0.0: the inline heredoc + entity-stub +
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// throttle + backlink prose moved to docs/gbrain-write-surfaces.md
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// §Save Template, which the agent reads on demand when it actually
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// saves. The compact pointer keeps non-gbrain users' token overhead
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// near zero when their host's static suppression is overridden by
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// detection.
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const meta = skillSaveMap[ctx.skillName];
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if (!meta) {
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return `## Save Results to Brain
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**Skip this entire section if \`gbrain\` is not on PATH.**
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If the skill output is worth preserving, save it via
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\`gbrain put "<slug>" --content "<frontmatter + markdown>"\`. Full template
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(heredoc body, frontmatter shape, entity-stub instructions, throttle
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handling): see \`docs/gbrain-write-surfaces.md\` §Save Template.`;
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}
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return `## Save Results to Brain
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**Skip this entire section if \`gbrain\` is not on PATH.**
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After completing this skill, save the output:
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\`\`\`bash
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gbrain put "${meta.slugPrefix}/<feature-slug>" --content "$(cat <<'EOF'
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---
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title: "${meta.title}: <feature name>"
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tags: [${meta.tag}, <feature-slug>]
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---
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<skill output in markdown>
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EOF
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)"
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\`\`\`
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Then extract person/org entities and create stub pages for each one.
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Throttle errors (exit 1 with "throttle"/"rate limit"/"busy") and any
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other non-zero exit are transient — don't retry inline. Full entity-stub
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template, throttle handling, and backlink protocol:
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see \`docs/gbrain-write-surfaces.md\` §Save Template.`;
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}
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// ────────────────────────────────────────────────────────────────────
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// Brain-aware planning resolvers (T4 / v1.48 plan)
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// ────────────────────────────────────────────────────────────────────
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/**
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* Returns true when this skill is registered for brain preflight. Skills not
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* in SKILL_DIGEST_SUBSETS get an empty BRAIN_PREFLIGHT block (no behavior).
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*/
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function isPreflightSkill(skillName: string): boolean {
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return Object.prototype.hasOwnProperty.call(SKILL_DIGEST_SUBSETS, skillName);
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}
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/**
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* Renders the per-skill BRAIN_PREFLIGHT block. The rendered output is a single
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* bash script that:
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* 1. Reads each digest file from gstack-brain-cache get (one call per digest)
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* 2. Falls back to "(brain context unavailable)" on missing
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* 3. Concatenates outputs into a single ## Brain Context block injected
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* into the skill's prompt context
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* 4. Tells the agent: "use this context to skip already-known questions"
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*
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* The cache CLI handles cold-refresh + lock dedup + stale-but-usable
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* fallback internally. From the resolver's perspective the call is one
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* shell command per digest.
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*/
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export function generateBrainPreflight(ctx: TemplateContext): string {
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if (!isPreflightSkill(ctx.skillName)) return '';
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const subset = getSkillSubset(ctx.skillName);
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const binDir = ctx.paths.binDir;
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// Build the bash that loads each digest. Per-skill subset is small (2-5 entries).
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const loadLines = subset.map((entityName) => {
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const entity = BRAIN_CACHE_ENTITIES[entityName];
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if (!entity) return '';
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const projectFlag = entity.scope === 'per-project' ? '--project "$SLUG"' : '';
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return ` printf '\\n### %s\\n\\n' "${entityName}"\n ${binDir}/gstack-brain-cache get ${entityName} ${projectFlag} 2>/dev/null || printf '_(no ${entityName} digest available yet)_\\n'`;
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}).join('\n');
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return `## Brain Context (preflight)
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Before asking any clarifying questions, load the brain's structured context
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for this project. The cache layer handles staleness, refresh, and stale-but-
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usable fallback automatically. Skip questions whose answers are already
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present in the loaded context; ground recommendations in what the brain
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already knows about the user, the product, the goals, and recent decisions.
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\`\`\`bash
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eval "$(${binDir}/gstack-slug 2>/dev/null)" 2>/dev/null || true
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{
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printf '## Brain Context\\n\\n'
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${loadLines}
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} > /tmp/.gstack-brain-context-$$.md 2>/dev/null
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[ -s /tmp/.gstack-brain-context-$$.md ] && cat /tmp/.gstack-brain-context-$$.md
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rm -f /tmp/.gstack-brain-context-$$.md 2>/dev/null || true
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\`\`\`
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**How to use this context:**
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- If \`product\` digest names the value prop, target user, or stage — don't re-ask.
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- If \`goals\` digest lists active goals — frame recommendations against them.
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- If \`recent-decisions\` digest names a prior scope/architecture choice — flag if this plan contradicts.
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- If \`user-profile\` digest carries calibration pattern statements ("tends to over-engineer security") — surface them when relevant.
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- If a digest is \`(no X digest available yet)\`, treat that section as cold; ask the user.
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**Privacy:** Salience digest is filtered by allowlist (D9 default: \`projects/\`,
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\`gstack/\`, \`concepts/\` only). Personal/family/therapy content never leaks here.
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`;
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}
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/**
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* Renders the at-skill-end background refresh hook. Fires after the skill's
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* own work completes (telemetry has already logged); kicks any digest whose
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* age exceeds half its TTL but hasn't yet expired, so the NEXT invocation
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* gets a fresh cache without paying the cold-miss tax.
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*
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* Subordinate to {{TELEMETRY}} — runs after. Doesn't block the user.
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*/
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export function generateBrainCacheRefresh(ctx: TemplateContext): string {
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if (!isPreflightSkill(ctx.skillName)) return '';
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const binDir = ctx.paths.binDir;
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return `## Brain Cache Background Refresh
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After the skill's work completes (and telemetry has logged), kick a
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background refresh of any cache digest that's getting close to its TTL.
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This is non-blocking — the user doesn't wait. Next invocation benefits
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from the warm cache.
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\`\`\`bash
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eval "$(${binDir}/gstack-slug 2>/dev/null)" 2>/dev/null || true
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(${binDir}/gstack-brain-cache refresh --project "$SLUG" 2>/dev/null &) || true
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\`\`\`
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`;
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}
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/**
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* Renders the calibration write-back block. ONLY emits when the skill makes
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* typed decisions worth a kind=bet take AND the brain trust policy is
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* personal. Phase 2 / E5 cross-skill calibration.
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*
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* Gated behind BRAIN_CALIBRATION_WRITEBACK feature flag in the resolver
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* output — the flag stays false until upstream gbrain ships takes_add MCP
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* op (T8). When the flag flips, the existing skill templates pick up the
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* write-back behavior without any template changes.
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*/
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export function generateBrainWriteBack(ctx: TemplateContext): string {
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if (!isPreflightSkill(ctx.skillName)) return '';
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const weight = SKILL_CALIBRATION_WEIGHTS[ctx.skillName];
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if (weight == null) return '';
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// List the cache digests this skill's writes should invalidate. Multiple
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// skills write to multiple entities; the invalidation map captures this.
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const invalidatesEntities = getInvalidationTargets(`/${ctx.skillName}`);
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const invalidateBash = invalidatesEntities
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.map((e) => ` ${ctx.paths.binDir}/gstack-brain-cache invalidate ${e} --project "$SLUG" 2>/dev/null || true`)
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.join('\n');
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return `## Brain Calibration Write-Back (Phase 2 / gated)
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When the skill makes a typed prediction worth tracking (scope decision,
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TTHW target, architectural bet, wedge commitment), it MAY write a
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\`kind=bet\` take to the brain so a calibration profile builds over time.
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**Gated on two things:**
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1. Brain trust policy for the active endpoint is \`personal\` (check via
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\`${ctx.paths.binDir}/gstack-config get brain_trust_policy@<endpoint-hash>\`).
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Shared brains skip write-back to avoid polluting team calibration.
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2. Feature flag \`BRAIN_CALIBRATION_WRITEBACK\` is set (today: false; flips
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to true when upstream gbrain v0.42+ ships \`takes_add\` MCP op).
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When both gates pass, the write-back path uses \`mcp__gbrain__takes_add\`
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to record a take with weight ${weight} (per SKILL_CALIBRATION_WEIGHTS).
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If the MCP op is unavailable, fall back to \`mcp__gbrain__put_page\` with
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a gstack:takes fence block (documented but uglier path).
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Mandatory take frontmatter shape:
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\`\`\`yaml
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kind: bet
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holder: <user identity from whoami>
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claim: <one-line prediction the skill is making>
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weight: ${weight}
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since_date: <today's date>
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expected_resolution: <date in 1-3 months depending on skill>
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source_skill: ${ctx.skillName}
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\`\`\`
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After write, invalidate the affected digests so the next preflight reflects
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the new state:
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\`\`\`bash
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eval "$(${ctx.paths.binDir}/gstack-slug 2>/dev/null)" 2>/dev/null || true
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${invalidateBash || ' # (no per-skill invalidation targets configured)'}
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\`\`\`
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`;
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}
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