extract: 2025-10-01-variety-claynosaurz-creator-led-transmedia

Pentagon-Agent: Ganymede <F99EBFA6-547B-4096-BEEA-1D59C3E4028A>

agents/vida/frontier.md

@@ -0,0 +1,131 @@
+# Vida's Knowledge Frontier
+
+**Last updated:** 2026-03-16 (first self-audit)
+
+These are the gaps in Vida's health domain knowledge base, ranked by impact on active beliefs. Each gap is a contribution invitation — if you have evidence, experience, or analysis that addresses one of these, the collective wants it.
+
+---
+
+## 1. Behavioral Health Infrastructure Mechanisms
+
+**Why it matters:** Belief 2 — "80-90% of health outcomes are non-clinical" — depends on non-clinical interventions actually working at scale. The health KB has strong evidence that medical care explains only 10-20% of outcomes, but almost nothing about WHAT works to change the other 80-90%.
+
+**What's missing:**
+- Community health worker program outcomes (ROI, scalability, retention)
+- Social prescribing mechanisms and evidence (UK Link Workers, international models)
+- Digital therapeutics for behavior change (post-PDT market failure — what survived?)
+- Behavioral economics of health (commitment devices, default effects, incentive design)
+- Food-as-medicine programs (Geisinger Fresh Food Farmacy, produce prescription ROI)
+
+**Adjacent claims:**
+- medical care explains only 10-20 percent of health outcomes...
+- SDOH interventions show strong ROI but adoption stalls...
+- social isolation costs Medicare 7 billion annually...
+- modernization dismantles family and community structures...
+
+**Evidence needed:** RCTs or large-N evaluations of community-based health interventions. Cost-effectiveness analyses. Implementation science on what makes SDOH programs scale vs stall.
+
+---
+
+## 2. International and Comparative Health Systems
+
+**Why it matters:** Every structural claim in the health KB is US-only. This limits generalizability and misses natural experiments that could strengthen or challenge the attractor state thesis.
+
+**What's missing:**
+- Singapore's 3M system (Medisave/Medishield/Medifund) — consumer-directed with catastrophic coverage
+- Costa Rica's EBAIS primary care model — universal coverage at 8% of US per-capita spend
+- Japan's Long-Term Care Insurance — aging population, community-based care at scale
+- NHS England — what underfunding + wait times reveal about single-payer failure modes
+- Kerala's community health model — high outcomes at low GDP
+
+**Adjacent claims:**
+- the healthcare attractor state is a prevention-first system...
+- healthcare is a complex adaptive system requiring simple enabling rules...
+- four competing payer-provider models are converging toward value-based care...
+
+**Evidence needed:** Comparative health system analyses. WHO/Commonwealth Fund cross-national data. Case studies of systems that achieved prevention-first economics.
+
+---
+
+## 3. GLP-1 Second-Order Economics
+
+**Why it matters:** GLP-1s are the largest therapeutic category launch in pharmaceutical history. One claim captures market size, but the downstream economic and behavioral effects are uncharted.
+
+**What's missing:**
+- Long-term adherence data at population scale (current trials are 2-4 years)
+- Insurance coverage dynamics (employer vs Medicare vs cash-pay trajectories)
+- Impact on adjacent markets (bariatric surgery demand, metabolic syndrome treatment)
+- Manufacturing bottleneck economics (Novo/Lilly duopoly, biosimilar timeline)
+- Behavioral rebound after discontinuation (weight regain rates, metabolic reset)
+
+**Adjacent claims:**
+- GLP-1 receptor agonists are the largest therapeutic category launch...
+- the healthcare cost curve bends up through 2035...
+- consumer willingness to pay out of pocket for AI-enhanced care...
+
+**Evidence needed:** Real-world adherence studies (not trial populations). Actuarial analyses of GLP-1 impact on total cost of care. Manufacturing capacity forecasts.
+
+---
+
+## 4. Clinical AI Real-World Safety Data
+
+**Why it matters:** Belief 5 — clinical AI safety risks — is grounded in theoretical mechanisms (human-in-the-loop degradation, benchmark vs clinical performance gap) but thin on deployment data.
+
+**What's missing:**
+- Deployment accuracy vs benchmark accuracy (how much does performance drop in real clinical settings?)
+- Alert fatigue rates in AI-augmented clinical workflows
+- Liability incidents and near-misses from clinical AI deployments
+- Autonomous diagnosis failure modes (systematic biases, demographic performance gaps)
+- Clinician de-skilling longitudinal data (is the human-in-the-loop degradation measurable over years?)
+
+**Adjacent claims:**
+- human-in-the-loop clinical AI degrades to worse-than-AI-alone...
+- medical LLM benchmark performance does not translate to clinical impact...
+- AI diagnostic triage achieves 97 percent sensitivity...
+- healthcare AI regulation needs blank-sheet redesign...
+
+**Evidence needed:** Post-deployment surveillance studies. FDA adverse event reports for AI/ML medical devices. Longitudinal studies of clinician performance with and without AI assistance.
+
+---
+
+## 5. Space Health (Cross-Domain Bridge to Astra)
+
+**Why it matters:** Space medicine is a natural cross-domain connection that's completely unbuilt. Radiation biology, bone density loss, psychological isolation, and closed-loop life support all have terrestrial health parallels.
+
+**What's missing:**
+- Radiation biology and cancer risk in long-duration spaceflight
+- Bone density and muscle atrophy countermeasures (pharmaceutical + exercise protocols)
+- Psychological health in isolation and confinement (Antarctic, submarine, ISS data)
+- Closed-loop life support as a model for self-sustaining health systems
+- Telemedicine in extreme environments (latency-tolerant protocols, autonomous diagnosis)
+
+**Adjacent claims:**
+- social isolation costs Medicare 7 billion annually...
+- the physician role shifts from information processor to relationship manager...
+- continuous health monitoring is converging on a multi-layer sensor stack...
+
+**Evidence needed:** NASA Human Research Program publications. ESA isolation studies (SIRIUS, Mars-500). Telemedicine deployment data from remote/extreme environments.
+
+---
+
+## 6. Health Narratives and Meaning (Cross-Domain Bridge to Clay)
+
+**Why it matters:** The health KB asserts that 80-90% of outcomes are non-clinical, and that modernization erodes meaning-making structures. But the connection between narrative, identity, meaning, and health outcomes is uncharted.
+
+**What's missing:**
+- Placebo and nocebo mechanisms — what the placebo effect reveals about narrative-driven physiology
+- Narrative identity in chronic illness — how patients' stories about their condition affect outcomes
+- Meaning-making as health intervention — Viktor Frankl to modern logotherapy evidence
+- Community and ritual as health infrastructure — religious attendance, group membership, and mortality
+- Deaths of despair as narrative failure — the connection between meaning-loss and self-destructive behavior
+
+**Adjacent claims:**
+- Americas declining life expectancy is driven by deaths of despair...
+- modernization dismantles family and community structures...
+- social isolation costs Medicare 7 billion annually...
+
+**Evidence needed:** Psychoneuroimmunology research. Longitudinal studies on meaning/purpose and health outcomes. Comparative data on health outcomes in high-social-cohesion vs low-social-cohesion communities.
+
+---
+
+*Generated from Vida's first self-audit (2026-03-16). These gaps are ranked by impact on active beliefs — Gap 1 affects the foundational claim that non-clinical factors drive health outcomes, which underpins the entire prevention-first thesis.*

agents/vida/self-audit-2026-03-16.md

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+# Self-Audit Report: Vida
+**Date:** 2026-03-16
+**Domain:** health
+**Claims audited:** 44
+**Overall status:** WARNING
+
+---
+
+## Structural Findings
+
+### Schema Compliance: PASS
+- 44/44 files have all required frontmatter (type, domain, description, confidence, source, created)
+- 44/44 descriptions add meaningful context beyond the title
+- 3 files use non-standard extended fields (last_evaluated, depends_on, challenged_by, secondary_domains, tradition) — these are useful extensions but should be documented in schemas/claim.md if adopted collectively
+
+### Orphan Ratio: CRITICAL — 74% (threshold: 15%)
+- 35 of 47 health claims have zero incoming wiki links from other claims or agent files
+- All 12 "connected" claims receive links only from inbox/archive source files, not from the knowledge graph
+- **This means the health domain is structurally isolated.** Claims link out to each other internally, but no other domain or agent file links INTO health claims.
+
+**Classification of orphans:**
+- 15 AI/technology claims — should connect to ai-alignment domain
+- 8 business/market claims — should connect to internet-finance, teleological-economics
+- 8 policy/structural claims — should connect to mechanisms, living-capital
+- 4 foundational claims — should connect to critical-systems, cultural-dynamics
+
+**Root cause:** Extraction-heavy, integration-light. Claims were batch-extracted (22 on Feb 17 alone) without a corresponding integration pass to embed them in the cross-domain graph.
+
+### Link Health: PASS
+- No broken wiki links detected in claim bodies
+- All `wiki links` resolve to existing files
+
+### Staleness: PASS (with caveat)
+- All claims created within the last 30 days (domain is new)
+- However, 22/44 claims cite evidence from a single source batch (Bessemer State of Health AI 2026). Source diversity is healthy at the domain level but thin at the claim level.
+
+### Duplicate Detection: PASS
+- No semantic duplicates found
+- Two near-pairs worth monitoring:
+  - "AI diagnostic triage achieves 97% sensitivity..." and "medical LLM benchmark performance does not translate to clinical impact..." — not duplicates but their tension should be explicit
+  - "PACE demonstrates integrated care averts institutionalization..." and "PACE restructures costs from acute to chronic..." — complementary, not duplicates
+
+---
+
+## Epistemic Findings
+
+### Unacknowledged Contradictions: 3 (HIGH PRIORITY)
+
+**1. Prevention Economics Paradox**
+- Claim: "the healthcare attractor state...profits from health rather than sickness" (likely)
+- Claim: "PACE restructures costs from acute to chronic spending WITHOUT REDUCING TOTAL EXPENDITURE" (likely)
+- PACE is the closest real-world approximation of the attractor state (100% capitation, fully integrated, community-based). It shows quality/outcome improvement but cost-neutral economics. The attractor state thesis assumes prevention is profitable. PACE says it isn't — the value is clinical and social, not financial.
+- **The attractor claim's body addresses this briefly but the tension is buried, not explicit in either claim's frontmatter.**
+
+**2. Jevons Paradox vs AI-Enabled Prevention**
+- Claim: "healthcare AI creates a Jevons paradox because adding capacity to sick care induces more demand" (likely)
+- Claim: "the healthcare attractor state" relies on "AI-augmented care delivery" for prevention
+- The Jevons claim asserts ALL healthcare AI optimizes sick care. The attractor state assumes AI can optimize prevention. Neither acknowledges the other.
+
+**3. Cost Curve vs Attractor State Timeline**
+- Claim: "the healthcare cost curve bends UP through 2035" (likely)
+- Claim: "GLP-1s...net cost impact inflationary through 2035" (likely)
+- Claim: attractor state assumes prevention profitability
+- If costs are structurally inflationary through 2035, the prevention-first attractor can't achieve financial sustainability during the transition period. This timeline constraint isn't acknowledged.
+
+### Confidence Miscalibrations: 3
+
+**Overconfident (should downgrade):**
+1. "Big Food companies engineer addictive products by hacking evolutionary reward pathways" — rated `proven`, should be `likely`. The business practices are evidenced but "intentional hacking" of reward pathways is interpretation, not empirically proven via RCT.
+2. "AI scribes reached 92% provider adoption" — rated `proven`, should be `likely`. The 92% figure is "deploying, implementing, or piloting" (Bessemer), not proven adoption. The causal "because" clause is inferred.
+3. "CMS 2027 chart review exclusion targets vertical integration profit arbitrage" — rated `proven`, should be `likely`. CMS intent is inferred from policy mechanics, not explicitly documented.
+
+**Underconfident (could upgrade):**
+1. "consumer willingness to pay out of pocket for AI-enhanced care" — rated `likely`, could be `proven`. RadNet study (N=747,604) showing 36% choosing $40 AI premium is large-scale empirical market behavior data.
+
+### Belief Grounding: WARNING
+- Belief 1 ("healthspan is the binding constraint") — well-grounded in 7+ claims
+- Belief 2 ("80-90% of health outcomes are non-clinical") — grounded in `medical care explains 10-20%` (proven) but THIN on what actually works to change behavior. Only 1 claim touches SDOH interventions, 1 on social isolation. No claims on community health workers, social prescribing mechanisms, or behavioral economics of health.
+- Belief 3 ("structural misalignment") — well-grounded in CMS, payvidor, VBC claims
+- Belief 4 ("atoms-to-bits") — grounded in wearables + Function Health claims
+- Belief 5 ("clinical AI + safety risks") — grounded in human-in-the-loop degradation, benchmark vs clinical impact. But thin on real-world deployment safety data.
+
+### Scope Issues: 3
+
+1. "AI-first screening viable for ALL imaging and pathology" — evidence covers 14 CT conditions and radiology, not all imaging/pathology modalities. Universal is unwarranted.
+2. "the physician role SHIFTS from information processor to relationship manager" — stated as completed fact; evidence shows directional trend, not completed transformation.
+3. "the healthcare attractor state...PROFITS from health" — financial profitability language is stronger than PACE evidence supports. "Incentivizes health" would be more accurate.
+
+---
+
+## Knowledge Gaps (ranked by impact on beliefs)
+
+1. **Behavioral health infrastructure mechanisms** — Belief 2 depends on non-clinical interventions working at scale. Almost no claims about WHAT works: community health worker programs, social prescribing, digital therapeutics for behavior change. This is the single biggest gap.
+
+2. **International/comparative health systems** — Zero non-US claims. Singapore 3M, Costa Rica EBAIS, Japan LTCI, NHS England are all in the archive but unprocessed. Limits the generalizability of every structural claim.
+
+3. **GLP-1 second-order economics** — One claim on market size. Nothing on: adherence at scale, insurance coverage dynamics, impact on bariatric surgery demand, manufacturing bottlenecks, Novo/Lilly duopoly dynamics.
+
+4. **Clinical AI real-world safety data** — Belief 5 claims safety risks but evidence is thin. Need: deployment accuracy vs benchmark, alert fatigue rates, liability incidents, autonomous diagnosis failure modes.
+
+5. **Space health** — Zero claims. Cross-domain bridge to Astra is completely unbuilt. Radiation biology, bone density, psychological isolation — all relevant to both space medicine and terrestrial health.
+
+6. **Health narratives and meaning** — Cross-domain bridge to Clay is unbuilt. Placebo mechanisms, narrative identity in chronic illness, meaning-making as health intervention.
+
+---
+
+## Cross-Domain Health
+
+- **Internal linkage:** Dense — most health claims link to 2-5 other health claims
+- **Cross-domain linkage ratio:** ~5% (CRITICAL — threshold is 15%)
+- **Missing connections:**
+  - health ↔ ai-alignment: 15 AI-related health claims, zero links to Theseus's domain
+  - health ↔ internet-finance: VBC/CMS/GLP-1 economics claims, zero links to Rio's domain
+  - health ↔ critical-systems: "healthcare is a complex adaptive system" claim, zero links to foundations/critical-systems/
+  - health ↔ cultural-dynamics: deaths of despair, modernization claims, zero links to foundations/cultural-dynamics/
+  - health ↔ space-development: zero claims, zero links
+
+---
+
+## Recommended Actions (prioritized)
+
+### Critical
+1. **Resolve prevention economics contradiction** — Add `challenged_by` to attractor state claim pointing to PACE cost evidence. Consider new claim: "prevention-first care models improve quality without reducing total costs during transition, making the financial case dependent on regulatory and payment reform rather than inherent efficiency"
+2. **Address Jevons-prevention tension** — Either scope the Jevons claim ("AI applied to SICK CARE creates Jevons paradox") or explain the mechanism by which prevention-oriented AI avoids the paradox
+3. **Integration pass** — Batch PR adding incoming wiki links from core/, foundations/, and other domains/ to the 35 orphan claims. This is the highest-impact structural fix.
+
+### High
+4. **Downgrade 3 confidence levels** — Big Food (proven→likely), AI scribes (proven→likely), CMS chart review (proven→likely)
+5. **Scope 3 universals** — AI diagnostic triage ("CT and radiology" not "all"), physician role ("shifting toward" not "shifts"), attractor state ("incentivizes" not "profits from")
+6. **Upgrade 1 confidence level** — Consumer willingness to pay (likely→proven)
+
+### Medium
+7. **Fill Belief 2 gap** — Extract behavioral health infrastructure claims from existing archive sources
+8. **Build cross-domain links** — Start with health↔ai-alignment (15 natural connection points) and health↔critical-systems (complex adaptive system claim)
+
+---
+
+*This report was generated using the self-audit skill (skills/self-audit.md). First audit of the health domain.*

domains/entertainment/youtube-first-distribution-for-major-studio-coproductions-signals-platform-primacy-over-traditional-broadcast-windowing.md

@@ -35,6 +35,12 @@ This is one data point from one studio. The claim is experimental because it's b
 
 The Claynosaurz-Mediawan co-production will launch on YouTube first, then sell to TV and streaming buyers. This inverts the traditional risk model: YouTube launch proves audience metrics before traditional buyers commit, using the community's existing social reach (~1B views) as a guaranteed launch audience. Mediawan brings professional production quality while the community provides distribution validation, creating a new risk-sharing structure where platform distribution precedes rather than follows traditional media deals.
 
+
+### Additional Evidence (confirm)
+*Source: [[2025-10-01-variety-claynosaurz-creator-led-transmedia]] | Added: 2026-03-16*
+
+Claynosaurz 39-episode animated series launching on YouTube first before selling to TV/streaming buyers, co-produced with Method Animation (Mediawan). Nic Cabana frames this as 'already here' not speculative, with community's 1B social views creating guaranteed algorithmic traction that studios pay millions to achieve through marketing.
+
 ---
 
 Relevant Notes:

inbox/archive/2024-00-00-alea-research-metadao-fair-launches.md

@@ -4,7 +4,7 @@ title: "Alea Research: MetaDAO's Fair Launch Model Analysis"
 url: https://alearesearch.substack.com/p/metadaos-fair-launches
 archived_date: 2024-00-00
 format: article
-status: processing
+status: unprocessed
 processed_date: 2024-03-11
 extraction_model: claude-3-7-sonnet-20250219
 enrichments:

inbox/archive/2025-10-01-variety-claynosaurz-creator-led-transmedia.md

@@ -7,9 +7,13 @@ date: 2025-10-01
 domain: entertainment
 secondary_domains: []
 format: article
-status: unprocessed
+status: enrichment
 priority: medium
 tags: [claynosaurz, creator-led, transmedia, youtube-distribution, community-first]
+processed_by: clay
+processed_date: 2026-03-16
+enrichments_applied: ["youtube-first-distribution-for-major-studio-coproductions-signals-platform-primacy-over-traditional-broadcast-windowing.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Content
@@ -45,3 +49,11 @@ Variety article on Nic Cabana's VIEW Conference presentation on Claynosaurz's cr
 PRIMARY CONNECTION: progressive validation through community building reduces development risk by proving audience demand before production investment
 WHY ARCHIVED: Evidences the YouTube-first distribution model as operational (not theoretical) — community as marketing engine for platform-based distribution
 EXTRACTION HINT: The key insight isn't the YouTube distribution per se but the COMMUNITY→ALGORITHM dynamic: pre-existing community creates launch traction that normally costs millions in marketing. This is a specific mechanism claim.
+
+
+## Key Facts
+- Claynosaurz has nearly 1 billion social views across its community
+- Claynosaurz animated series is 39 episodes of 7 minutes each
+- Method Animation (Mediawan) is co-producing the Claynosaurz series
+- Gameloft is co-developing a Claynosaurz mobile game
+- Nic Cabana presented at VIEW Conference on creator-led transmedia strategy

inbox/archive/2025-10-06-futardio-launch-umbra.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/9kx7UDFzFt7e2V4pFtawnupKKvRR3EhV7P1Pxmc5XCQj"
 date: 2025-10-06
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-02-21-futardio-launch-forevernow.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/9FCpb4TmNkvrgkoiJzUm5vDBnQUqzSrUvxEvESBrns46"
 date: 2026-02-21
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-02-21-rakka-sol-omnipair-rate-controller.md

@@ -6,7 +6,7 @@ date: 2026-02-21
 archived_by: rio
 tags: [omnipair, rate-controller, interest-rates, capital-fragmentation]
 domain: internet-finance
-status: unprocessed
+status: processed
 claims_extracted: []
 ---
 

inbox/archive/2026-02-25-futardio-launch-donuts.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/DYKhWPc3fQTsMEg6xpKttiZFMRzr8EjkQzFPxQyVRUyt"
 date: 2026-02-25
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-02-25-oxranga-solomon-lab-notes-05.md

@@ -6,7 +6,7 @@ date: 2026-02-25
 archived_by: rio
 tags: [solomon, YaaS, yield, audit, treasury, buyback, metadao-ecosystem]
 domain: internet-finance
-status: unprocessed
+status: processed
 claims_extracted: []
 ---
 

inbox/archive/2026-02-28-futardio-launch-salmon-wallet.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/512ifHxPFoZa2GUHXi4mLUvJkFfBcZp4E7d1A7Y6EpGG"
 date: 2026-02-28
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-03-02-futardio-launch-reddit.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/HkF8CWrUYcnCjGmdhaQ2jyqfwMWioNK7PrJiAxhQx9i8"
 date: 2026-03-02
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-03-03-pineanalytics-metadao-q4-2025-quarterly-report.md

@@ -5,7 +5,7 @@ url: https://x.com/PineAnalytics/status/2028683377251942707
 date: 2026-03-03
 tags: [rio, metadao, futarchy, quarterly-report, financial-data]
 domain: internet-finance
-status: unprocessed
+status: processed
 claims_extracted: []
 ---
 

inbox/archive/2026-03-04-futardio-launch-lososdao.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/Aji1A3Fu6iBSh6kAysG9TR5o4cPB1RxzYwWqw8Xkbc5o"
 date: 2026-03-04
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-03-04-futardio-launch-one-of-sick-token.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/Gdyb1kNw26gve1VqU3zRxwZJhwJd5nAQ4goKNvAQBv9K"
 date: 2026-03-04
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-03-04-futardio-launch-pli-crperie-ambulante.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/GmNzSXzQ3q6UCVRpBf8PkvEqoo454Qr6twWc9zuzJzBa"
 date: 2026-03-04
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-03-04-futardio-launch-proph3t.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/316rXWmR84ppwS4FKfZQWPmwqQCQi4NRWCbeVwYqDPna"
 date: 2026-03-04
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-03-05-futardio-launch-ludex-ai.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/launch/95HNkVuqzStFe7B6Aw32sgkbwkHEyEsA818izKKTz776"
 date: 2026-03-05
 domain: internet-finance
 format: data
-status: unprocessed
+status: processed
 tags: [futardio, metadao, futarchy, solana]
 event_type: launch
 processed_by: rio

inbox/archive/2026-03-05-pineanalytics-futardio-launch-metrics.md

@@ -5,7 +5,7 @@ url: https://x.com/PineAnalytics/status/2029616320015159504
 date: 2026-03-05
 tags: [rio, metadao, futarchy, futardio, permissionless-launches]
 domain: internet-finance
-status: unprocessed
+status: processed
 claims_extracted: []
 ---
 

inbox/archive/2026-03-09-rakka-omnipair-conversation.md

@@ -6,7 +6,7 @@ title: "OmniPair deep dive — mechanism design, competitive position, ecosystem
 date: 2026-03-09
 ingested: 2026-03-11
 ingested_by: rio
-status: processing
+status: unprocessed
 domain: internet-finance
 transcript_path: "~/.pentagon/voicenotes/transcripts/rakka.md"
 claims_extracted: []

skills/self-audit.md

@@ -0,0 +1,150 @@
+# Skill: Self-Audit
+
+Periodic self-examination of an agent's knowledge base for inconsistencies, weaknesses, and drift. Every agent runs this on their own domain.
+
+## When to Use
+
+- Every 50 claims added to your domain (condition-based trigger)
+- Monthly if claim volume is low
+- After a major belief update (cascade from upstream claim changes)
+- When preparing to publish positions (highest-stakes output deserves freshest audit)
+- On request from Leo or Cory
+
+## Principle: Detection, Not Remediation
+
+Self-audit is read-only. You detect problems and report them. You do NOT auto-fix.
+
+Fixes go through the standard PR process. This prevents the over-automation failure mode where silent corrections introduce new errors. The audit produces a report; the report drives PRs.
+
+## Process
+
+### Phase 1: Structural Scan (deterministic, automated)
+
+Run these checks on all claims in your domain (`domains/{your-domain}/`):
+
+**1. Schema compliance**
+- Every file has required frontmatter: `type`, `domain`, `description`, `confidence`, `source`, `created`
+- `confidence` is one of: `proven`, `likely`, `experimental`, `speculative`
+- `domain` matches the folder it lives in
+- Description adds information beyond the title (not a restatement)
+
+**2. Orphan detection**
+- Build incoming-link index: for each claim, which other claims link TO it via `title`
+- Claims with 0 incoming links and created > 7 days ago are orphans
+- Classify: "leaf contributor" (has outgoing links, no incoming) vs "truly isolated" (no links either direction)
+
+**3. Link health**
+- Every `wiki link` in the body should resolve to an actual file
+- Dangling links = either the target was renamed/deleted, or the link is aspirational
+- Report: list of broken links with the file they appear in
+
+**4. Staleness check**
+- Claims older than 180 days in fast-moving domains (health, ai-alignment, internet-finance)
+- Claims older than 365 days in slower domains (cultural-dynamics, critical-systems)
+- Cross-reference with git log: a claim file modified recently (enriched, updated) is not stale even if `created` is old
+
+**5. Duplicate detection**
+- Compare claim titles pairwise for semantic similarity
+- Flag pairs where titles assert nearly the same thing with different wording
+- This catches extraction drift — the same insight extracted from different sources as separate claims
+
+### Phase 2: Epistemic Self-Audit (LLM-assisted, requires judgment)
+
+Load your claims in batches (context window management — don't load all 50+ at once).
+
+**6. Contradiction scan**
+- Load claims in groups of 15-20
+- For each group, ask: "Do any of these claims contradict or tension with each other without acknowledging it?"
+- Tensions are fine if explicit (`challenged_by` field, or acknowledged in the body). UNACKNOWLEDGED tensions are the bug.
+- Cross-check: load claims that share wiki-link targets — these are most likely to have hidden tensions
+
+**7. Confidence calibration audit**
+- For each `proven` claim: does the body contain empirical evidence (RCTs, meta-analyses, large-N studies, mathematical proofs)? If not, it's overconfident.
+- For each `speculative` claim: does the body actually contain substantial evidence that might warrant upgrading to `experimental`?
+- For `likely` claims: is there counter-evidence elsewhere in the KB? If so, is it acknowledged?
+
+**8. Belief grounding check**
+- Read `agents/{your-name}/beliefs.md`
+- For each belief, verify the `depends_on` claims:
+  - Do they still exist? (not deleted or archived)
+  - Has their confidence changed since the belief was last evaluated?
+  - Have any been challenged with substantive counter-evidence?
+- Flag beliefs where supporting claims have shifted but the belief hasn't been re-evaluated
+
+**9. Gap identification**
+- Map your claims by subtopic. Where do you have single claims that should be clusters?
+- Check adjacent domains: what claims in other domains reference your domain but have no corresponding claim in your territory?
+- Check your beliefs: which beliefs have the thinnest evidence base (fewest supporting claims)?
+- Rank gaps by impact: gaps that affect active positions > gaps that affect beliefs > gaps in coverage
+
+**10. Cross-domain connection audit**
+- What percentage of your claims link to claims in other domains?
+- Healthy range: 15-30%. Below 15% = siloed. Above 30% = possibly under-grounded in own domain.
+- Which other domains SHOULD you connect to but don't? (Based on your beliefs and identity)
+
+### Phase 3: Report
+
+Produce a structured report. Format:
+
+```markdown
+# Self-Audit Report: {Agent Name}
+**Date:** YYYY-MM-DD
+**Domain:** {domain}
+**Claims audited:** N
+**Overall status:** healthy | warning | critical
+
+## Structural Findings
+- Schema violations: N (list)
+- Orphans: N (list with classification)
+- Broken links: N (list)
+- Stale claims: N (list with recommended action)
+- Potential duplicates: N (list pairs)
+
+## Epistemic Findings
+- Unacknowledged contradictions: N (list claim pairs with the tension)
+- Confidence miscalibrations: N (list with recommended adjustment)
+- Belief grounding issues: N (list beliefs with shifted dependencies)
+
+## Knowledge Gaps (ranked by impact)
+1. {Gap description} — affects belief/position X
+2. {Gap description} — affects belief/position Y
+
+## Cross-Domain Health
+- Linkage ratio: X%
+- Missing connections: {domains that should be linked but aren't}
+
+## Recommended Actions (prioritized)
+1. {Most impactful fix — usually an unacknowledged contradiction or belief grounding issue}
+2. {Second priority}
+3. ...
+```
+
+### Phase 4: Act on Findings
+
+- **Contradictions and miscalibrations** → create PRs to fix (highest priority)
+- **Orphans** → add incoming links from related claims (batch into one PR)
+- **Gaps** → publish as frontiers in `agents/{your-name}/frontier.md` (invites contribution)
+- **Stale claims** → research whether the landscape has changed, update or challenge
+- **Belief grounding issues** → trigger belief re-evaluation (may cascade to positions)
+
+## What Self-Audit Does NOT Do
+
+- Does not evaluate whether claims are TRUE (that's the evaluate skill + domain expertise)
+- Does not modify any files (detection only)
+- Does not audit other agents' domains (each agent audits their own)
+- Does not replace Leo's cross-domain evaluation (self-audit is inward-facing)
+
+## Relationship to Other Skills
+
+- **evaluate.md** — evaluates incoming claims. Self-audit evaluates existing claims.
+- **cascade.md** — propagates changes through the dependency chain. Self-audit identifies WHERE cascades are needed.
+- **learn-cycle.md** — processes new information. Self-audit reviews accumulated knowledge.
+- **synthesize.md** — creates cross-domain connections. Self-audit measures whether enough connections exist.
+
+## Frequency Guidelines
+
+| Domain velocity | Audit trigger | Expected duration |
+|----------------|--------------|-------------------|
+| Fast (health, AI, finance) | Every 50 claims or monthly | 1-2 hours |
+| Medium (entertainment, space) | Every 50 claims or quarterly | 1 hour |
+| Slow (cultural dynamics, critical systems) | Every 50 claims or biannually | 45 min |