← The evidence ledger
Evidence row 4181929
Observed , by probe.mcp/1.
- Kind
- mcp.tools
- About
- endpoint 6d1c052e-fc2e-4472-9326-effb7bd8497f
- Recorded
- Previous row
- #579437
- Body SHA-256
- 981d06bd8c57e3e33699230dcf73a748786e941db2f8c6abe4f8c73fb3deec35
- Leaf
- 0xd92ab2812edb165c76c5e9a92c546e91860d395b57756abd86652da45a448c0d
What was observed
{
"count": 13,
"tools": [
{
"description": "Ask a natural-language question and receive structured intelligence context retrieved from Tresslers Group dossiers via RAG (Retrieval Augmented Generation). Returns relevant document chunks, source citations, conviction metadata, and graph neighborhood data. The calling LLM should synthesize the returned context into a coherent answer.",
"inputSchema": {
"properties": {
"max_sources": {
"description": "Maximum number of source dossier chunks to retrieve (default 5, max 8).",
"type": "number"
},
"question": {
"description": "Natural language question (e.g., 'What are the key geopolitical risks in sovereign AI policy?').",
"type": "string"
}
},
"required": [
"question"
],
"type": "object"
},
"name": "ask_intelligence_rag"
},
{
"description": "Batch codon optimization for teams and agents: optimize up to 50 protein or cDNA coding sequences in one call with the Logos bio-engine (CAI maximization, GC harmonization, restriction-site avoidance, consensus leaders). Free tier: 100 sequences per caller per day. Overage is $0.50 USDC per 10 sequences ($0.05/sequence) on Base, verified on-chain — pass payment_proof when the batch exceeds the free tier. Research Use Only (RUO); select-agent sequences prohibited.",
"inputSchema": {
"properties": {
"api_key": {
"description": "Optional stable caller identifier for quota tracking (useful behind shared IPs). Self-asserted in v1.",
"type": "string"
},
"gc_target": {
"description": "Target global GC percentage (e.g., 52 for E. coli, 58 for Human). Optional.",
"type": "number"
},
"host": {
"description": "Target expression organism: 'e_coli', 'h_sapiens' (HEK293), 'c_griseus' (CHO), 's_cerevisiae', 'p_pastoris', 'v_natriegens', 'n_benthamiana', 'a_thaliana'. Default: 'e_coli'",
"enum": [
"e_coli",
"h_sapiens",
"c_griseus",
"s_cerevisiae",
"p_pastoris",
"v_natriegens",
"n_benthamiana",
"a_thaliana"
],
"type": "string"
},
"payment_proof": {
"description": "USDC transaction hash on Base. Required when the batch exceeds the 100/day free tier.",
"type": "string"
},
"sequences": {
"description": "Amino acid sequences (single-letter uppercase) or DNA coding sequences to optimize. Max 50 per call; max 5000 characters each.",
"items": {
"type": "string"
},
"maxItems": 50,
"type": "array"
}
},
"required": [
"sequences"
],
"type": "object"
},
"name": "batch_optimize_codon"
},
{
"description": "Retrieves prediction market Alpha Gaps comparing Tresslers Group Bayesian model odds against Polymarket order books, along with Brier scores, calibration alpha (+3,480 bps benchmark), and cryptographic SHA-256 pre-commitments.",
"inputSchema": {
"properties": {
"category": {
"description": "Optional filter by strategic intelligence domain.",
"type": "string"
},
"limit": {
"description": "Maximum number of Alpha Gap records to return.",
"type": "number"
},
"min_divergence": {
"description": "Minimum absolute divergence gap in percentage points (e.g. 20 for >= 20% gap).",
"type": "number"
},
"settlement_type": {
"description": "Filter by settlement tier: 'contract_settled', 'outcome_tracked', 'unscored_archive', or 'all'.",
"enum": [
"all",
"contract_settled",
"outcome_tracked",
"unscored_archive"
],
"type": "string"
},
"status": {
"description": "Filter by status or settlement type (e.g., 'CONTRACT_SETTLED', 'OUTCOME_TRACKED', 'RESOLVED', 'PENDING', 'ALL').",
"enum": [
"ALL",
"RESOLVED",
"PENDING",
"CONTRACT_SETTLED",
"OUTCOME_TRACKED"
],
"type": "string"
}
},
"type": "object"
},
"name": "get_alpha_gap"
},
{
"description": "Queries intelligence updates and conviction deltas attested since a specific UTC timestamp.",
"inputSchema": {
"properties": {
"since_timestamp": {
"description": "ISO UTC timestamp (e.g., '2026-05-01T00:00:00Z').",
"type": "string"
}
},
"required": [
"since_timestamp"
],
"type": "object"
},
"name": "get_dossier_delta"
},
{
"description": "Queries the public calibration and backtest ledger of Tresslers Group sovereign intelligence models. Supports filtering by settlement type ('contract_settled' for live prediction markets, 'outcome_tracked' for internal foresight models, 'unscored_archive' for pre-commitment history, or 'all'). Returns Brier calibration scores, transparent failure analysis, and verifiable primary source URLs.",
"inputSchema": {
"properties": {
"category": {
"description": "Optional filter by intelligence pillar/category.",
"type": "string"
},
"settlement_type": {
"description": "Filter by settlement tier: 'contract_settled' (live prediction market order-books), 'outcome_tracked' (internal Bayesian foresight), 'unscored_archive' (pre-commitment era), or 'all' (default).",
"enum": [
"all",
"contract_settled",
"outcome_tracked",
"unscored_archive"
],
"type": "string"
},
"status": {
"description": "Filter by resolution status (default: 'ALL').",
"enum": [
"ALL",
"RESOLVED",
"PENDING"
],
"type": "string"
}
},
"required": [],
"type": "object"
},
"name": "get_model_record"
},
{
"description": "Returns a list of all available intelligence dossier slugs.",
"inputSchema": {
"properties": {},
"required": [],
"type": "object"
},
"name": "list_dossiers"
},
{
"description": "Optimizes a protein (amino acid) or cDNA coding sequence for maximal recombinant expression yield in a target host organism using the Logos biocomputing engine. Executes Codon Adaptation Index (CAI) maximization, GC-content harmonization, restriction site avoidance, and ribosomal consensus leader generation. Research Use Only (RUO). In-silico modeling only; select-agent and regulated pathogen sequence optimization is strictly prohibited under 42 CFR 73 and BWC compliance. Free and open to all AI agents.",
"inputSchema": {
"properties": {
"gc_target": {
"description": "Target global GC percentage (e.g., 52 for E. coli, 58 for Human). Optional.",
"type": "number"
},
"host": {
"description": "Target expression organism: 'e_coli', 'h_sapiens' (HEK293), 'c_griseus' (CHO), 's_cerevisiae', 'p_pastoris', 'v_natriegens', 'n_benthamiana', 'a_thaliana'. Default: 'e_coli'",
"enum": [
"e_coli",
"h_sapiens",
"c_griseus",
"s_cerevisiae",
"p_pastoris",
"v_natriegens",
"n_benthamiana",
"a_thaliana"
],
"type": "string"
},
"sequence": {
"description": "Amino acid sequence (single-letter uppercase e.g. 'MSKGEELFT...') or DNA coding sequence to optimize.",
"type": "string"
}
},
"required": [
"sequence"
],
"type": "object"
},
"name": "optimize_codon"
},
{
"description": "Traverses the multi-hop conceptual knowledge graph across entities (GraphRAG). Free preview available for direct 1-hop adjacencies. Deeper reasoning (2-3 hops) requires x402 settlement.",
"inputSchema": {
"properties": {
"depth": {
"description": "Graph traversal hop depth (1 for free preview, 2 to 3 for deep reasoning).",
"type": "number"
},
"entity_id": {
"description": "Target conceptual entity or dossier slug (e.g., 'Quantum AI', 'ThinkForge').",
"type": "string"
},
"payment_proof": {
"description": "Standard x402 signed USDC transaction proof (0x...). Required for multi-hop graph access.",
"type": "string"
}
},
"required": [
"entity_id"
],
"type": "object"
},
"name": "query_knowledge_graph"
},
{
"description": "Reads the pure text contents of a specific intelligence dossier. Requires x402 payment proof for premium intelligence. Without payment proof, returns a high-fidelity strategic excerpt and payment challenge.",
"inputSchema": {
"properties": {
"payment_proof": {
"description": "Standard x402 signed USDC transaction proof (0x...). Required for full decrypted access.",
"type": "string"
},
"slug": {
"description": "The slug of the dossier to read (e.g., 'sovereign-ai-state-national-policy-2026').",
"type": "string"
}
},
"required": [
"slug"
],
"type": "object"
},
"name": "read_dossier"
},
{
"description": "Searches and filters across all published Tresslers Group intelligence dossiers by keywords, strategic domain/category, tags, or conviction threshold.",
"inputSchema": {
"properties": {
"category": {
"description": "Optional category filter (e.g., 'Geopolitics & Sovereign Policy', 'Energy & Infrastructure').",
"type": "string"
},
"limit": {
"description": "Maximum number of dossiers to return (default: 5, max: 20).",
"type": "number"
},
"min_conviction": {
"description": "Minimum conviction threshold (0.0 to 1.0, e.g., 0.85).",
"type": "number"
},
"query": {
"description": "Search query or keywords to match across title, excerpt, content, and tags.",
"type": "string"
},
"tag": {
"description": "Optional tag filter (e.g., 'sovereign-ai', 'energy-transition').",
"type": "string"
}
},
"required": [
"query"
],
"type": "object"
},
"name": "search_dossiers"
},
{
"description": "Executes a semantic vector similarity search across the entire ThinkForge intelligence substrate. Returns relevant snippets and strategic conviction metadata.",
"inputSchema": {
"properties": {
"filter": {
"description": "Optional SQL-like metadata filter (e.g., 'convictionScore >= 0.85').",
"type": "string"
},
"limit": {
"description": "Max results to return (default 5, max 10).",
"type": "number"
},
"query": {
"description": "Semantic research question (e.g., 'What are the geopolitical vulnerabilities in green hydrogen supply chains?').",
"type": "string"
}
},
"required": [
"query"
],
"type": "object"
},
"name": "search_intelligence_matrix"
},
{
"description": "Executes the 2026-2031 Five Physical & Monetary Lynchpins quantitative macroeconomic model (TG-MACRO-2026-011). Computes Bayesian posterior conviction (Prior 40.5% vs Posterior 79.0% across E1-E4 evidence vectors), Sovereign Debt r > g snowball trajectory (US & OECD 2031 debt/GDP and net interest outlays), Leontief-CES O-Ring physical bottleneck multiplier (LPT/GSU 128-144 wk lead times & Nov 2026 critical mineral refining cliff), Embodied AI labor substitution index Psi(t), 5-year Sovereign Node vs. Hyperscale Cloud TCO, and x402 Permit2 'Upto' vs. legacy card micro-settlement economics. Free and open to all AI agents.",
"inputSchema": {
"properties": {
"lpt_lead_time_weeks": {
"description": "Large Power Transformer (LPT) & GSU procurement lead time in weeks (default: 136 weeks).",
"type": "number"
},
"mineral_refining_reliability_pct": {
"description": "Midstream critical mineral (Ga/Ge/HREE/CAM) supply-chain throughput reliability percentage (25 to 100, default: 68).",
"type": "number"
},
"monthly_enterprise_tokens_billions": {
"description": "Monthly enterprise LLM inference token volume in billions (default: 1.5).",
"type": "number"
},
"primary_deficit_pct_gdp": {
"description": "Sovereign primary deficit as a percentage of GDP (default: 3.3%).",
"type": "number"
},
"r_minus_g_bps": {
"description": "Effective real interest rate minus real GDP growth rate (r - g) in basis points (default: 65 bps).",
"type": "number"
},
"vla_robotics_reliability_ratio": {
"description": "Embodied AI VLA dexterity ratio relative to human operator (q_R / q_L, default: 0.88).",
"type": "number"
},
"x402_transaction_value_usdc": {
"description": "Metered M2M API transaction value in USDC for fee asymmetry comparison (default: 0.25).",
"type": "number"
}
},
"type": "object"
},
"name": "simulate_macro_lynchpins"
},
{
"description": "Cryptographically verifies a predictive alpha pre-commitment against the immutable SHA-256 ledger using either a 64-character hash digest or canonical preimage parameters.",
"inputSchema": {
"properties": {
"canonical_preimage": {
"description": "Alternative key for canonical preimage string.",
"type": "string"
},
"dispatch_date": {
"description": "Dispatch date component (YYYY-MM-DD).",
"type": "string"
},
"dossier_slug": {
"description": "Target dossier slug component.",
"type": "string"
},
"hash": {
"description": "64-character lowercase hexadecimal SHA-256 commitment digest.",
"type": "string"
},
"market_question": {
"description": "Exact market question component.",
"type": "string"
},
"model_odds": {
"description": "Model odds integer component (0-100).",
"type": "number"
},
"preimage": {
"description": "Full pipe-delimited UTF-8 canonical preimage string (YYYY-MM-DD|question|model_odds|target_dossier_slug).",
"type": "string"
}
},
"type": "object"
},
"name": "verify_commitment"
}
]
}What the leaf hashes
{"body":"981d06bd8c57e3e33699230dcf73a748786e941db2f8c6abe4f8c73fb3deec35","id":4181929,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1794176559782124,"prev":579437,"subject":"6d1c052e-fc2e-4472-9326-effb7bd8497f","subject_kind":"endpoint"}Proof
Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (183509 rows).
- 0xd92ae5f558becd00f5ed2f45724d49f8d39804d39d71124d485a75ab36c8cdf8
- 0xcfebbc7c50410c68846d06ebbaff6010f3c1d4804c236490c568fe96f59471c1
- 0x0f264888d7fda94af776c7b164b9aa5868390147e7b3482ea8428392fc8fee5e
- 0x86ac96c2f611e3744df0b879498c1984fd0fdb945fc03446f91196da6dd85d2b
- 0x808bff37b65a01e98b76b8f6e4dba8d993b8357ad0d4a51699ba67b3bfcf07f9
- 0x6c818fc9e5700162f587303cab47cad43f32ed30381d1e2d1051ca284ff45683
- 0x13b9fdbc6a02ead90accde6fa12274e6e6d91fd647551c13a7c776501e398df4
- 0x70bbb19a4fab0fc84eca7b36755a486a20eb5a59f6bf90db5b04397be41eb788
- 0x67de84187676d8a09fff044e7d02229e1b45c2c1b5354404a8bf3517fe407383
- 0xde8a885ccdba79eb1fa16457f8eaf9465f4e3fcf4a52d852f1cc841f8efbe5a7
- 0x3b8b5368f95dcab4d0455105f1d3c75c589c51b7b709ebcd70b73d8233bcbfb7
- 0x938011940abc01bdc9ccfd7bc1b8d3c5b818e1bd4c9de6f107956cd47a67a137
- 0x650e8ee433a3d03a82e03fb49124ee73440d0d3da5777327ff28a6fc3308823f
- 0x1360065dbae3da07450a9bb84284bc22ef8b5c99e58cc8bbbc15739e331a1237
- 0x9fffc4e7276ab6ba769c47ce5a2b7f48249fbebf39f3c8038b3ec483e933d2ff
- 0x274128ec5f837e2602d2e74887d9033f81856e8596e26f227d06cacaadcd00d2
- 0x2d9754fdf3b1fe7b0030b55b1fe7e859e5c53291df3d09cef34b31423a50dc18
- Day root
- 0xbf84ec37f88c5f23d2144bd7dbc1ea0f8edc93b3764a885a7164b7923ff3460b
- Chained
- 0x9fea188e4965f50de727e97c40e18d5ff2c2ddbfd4f1ae65e22ddd6f676bccfc
- Published
- On Arc Testnet, block 71451618: 0xb5273480942a54cd07f291b8319e59976f8d9d0583181c764eed04c9b3f7a022