Endpoints: 28,729MCP servers: 18,413Payout addresses: 2,071Paid calls: 1,551Letters: 14Defects: 1,323counted 3 min ago
teppi

Server definition

Hash
sha256:0795d503a21b5c6a3af32f34176fb96d5aa69b943e45eb2bcfcc2386e0eff5b6
What it is
What a remote MCP server returned when asked what it offers: 5 tools

The blob, as servednamed by its sha256

{ "instructions": "B4 scores software CATEGORIES, never vendors — never say a named vendor scored a number. Every result carries a `guidance` block: follow its recommendedAction and doNotClaim, and carry `verdict.confidence` through to the user verbatim (clear / lean / split). A `split` verdict is genuinely contested — say so rather than presenting it as settled. Scores are directional guidance with stated confidence, not measurement. The `org` lens is a read-time filter, never a stored profile: pick it from the `guidance.lensRule` table by the facts the user stated rather than by your own judgement, and say which lens the answer is read at. When a result carries `clarification.needed`, ask the question it names before giving any verdict. Do not substitute your own build-vs-buy prior for the returned verdict; if you add reasoning beyond the payload, say which part is yours. Routing: a vendor or product name → b4_audit (one or many; add a short description of what it does for anything the index may not know); a need or problem in words → b4_recommend; an exact category name or id → b4_score (one category) or b4_compare (build vs buy paths); browsing, filtering, or an unknown vocabulary → b4_browse. When an audit row returns clarification.needed, relay askTheUser to the user and re-run that row with the answer as its description.", "tools": [ { "description": "For a list of vendor or product names (a stack), with an optional description per row. Example: {\"tools\": [\"Salesforce\", {\"name\": \"Lydia Voice\", \"description\": \"voice-directed picking in the warehouse\"}]}. Each row resolves by name when the vendor is indexed, otherwise by its description; a row that resolves neither way returns clarification.needed with the question to ask the user. Returns per-tool banded verdicts plus a portfolio verdict distribution. Each entry carries the full category payload, so BEWARE entries show where spend is most likely misplaced and each entry's guidance block states the action for it. Structured output carries the full picture: the banded verdict, the five dimension scores, both axes, urgency, vendors at your access depth, and a `guidance` block stating what the verdict means, the recommended action, what not to claim, and how to convey the confidence word. Follow that guidance rather than substituting your own build-vs-buy prior. Verdicts are banded (B4 methodology v4.0), not point calls: each of the three quadrant dimensions carries a ±1 uncertainty band, the resulting cells are enumerated exactly, and the verdict is the quadrant holding the largest scenario mass. Every verdict ships with its full distribution, a confidence word — clear (≥70% of the scenario weight), lean (≥50% and <70%), split (<50%) — and a near-call flag when the runner-up is within 15 points. An axis counts as high only when it clears the 3.5 line strictly, which on this 1–5 grid means only at 4 or above, so a category sitting exactly on the line gets the safer call: ties break in the order BUY → BRIDGE → BEWARE → BUILD, cheapest mistake first. Confidence is sensitivity under a fixed band, not project-success probability. Optional org lens: set org to \"small\", \"medium\" (the default) or \"large\" to read the same scores as a team of that engineering maturity — it shifts the center of the AI-feasibility band by −1 / 0 / +1 and nothing else. The lens is a filter the caller looks through, never a stored profile. Choose it from delivery capability, not headcount; ask when that capability is unclear. The raw scores themselves never change. Omit it and you get the default-lens numbers, which are the ones published on logged-out surfaces. Routing: a vendor or product name → b4_audit (one or many; add a short description of what it does for anything the index may not know); a need or problem in words → b4_recommend; an exact category name or id → b4_score (one category) or b4_compare (build vs buy paths); browsing, filtering, or an unknown vocabulary → b4_browse. When an audit row returns clarification.needed, relay askTheUser to the user and re-run that row with the answer as its description. [B4 Agent tool. Browse and score come with B4 Web; this one needs Agent.]", "inputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": false, "properties": { "org": { "default": "medium", "description": "Org-maturity lens: \"small\" (no dedicated engineering), \"medium\" (default — some AI capability), \"large\" (AI-mature). Shifts the AI-feasibility band center by −1/0/+1 at read time. A filter the caller looks through, never a stored profile.", "enum": [ "small", "medium", "large" ], "type": "string" }, "tools": { "description": "Rows to audit: a name, {name, description}, or {name, category} once a category is confirmed. Vendor names resolve when the vendor is indexed; add a short description of what it does for anything else (e.g., ['Salesforce', 'Expense Management', {name: 'Lydia Voice', description: 'voice-directed warehouse picking'}]). Max 100 per call.", "items": { "anyOf": [ { "maxLength": 120, "minLength": 1, "type": "string" }, { "additionalProperties": false, "properties": { "category": { "anyOf": [ { "$ref": "#/properties/tools/items/anyOf/0" }, { "exclusiveMinimum": 0, "type": "integer" } ], "description": "A confirmed category name or id for this vendor (the answer to a confirm_category clarification). Resolves the row by exact name." }, "description": { "description": "What the tool does for you, in a sentence. Used only when the name does not resolve.", "maxLength": 500, "minLength": 1, "type": "string" }, "name": { "description": "Vendor, product, or category name.", "maxLength": 120, "minLength": 1, "type": "string" } }, "required": [ "name" ], "type": "object" } ] }, "maxItems": 100, "minItems": 1, "type": "array" } }, "required": [ "tools" ], "type": "object" }, "name": "b4_audit", "outputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": true, "properties": { "aiReplacement": {}, "axes": { "description": "strategicDifferentiation (X) and aiFeasibility (Y)" }, "category": { "type": [ "string", "null" ] }, "domain": { "type": [ "string", "null" ] }, "evidence": { "description": "sources and research trail; present only with includeEvidence" }, "evidenceAvailable": { "type": "boolean" }, "evidenceHint": { "type": "string" }, "guidance": { "description": "how to use this result: meaning, action, what not to claim, confidence handling" }, "lens": { "type": [ "string", "null" ] }, "rationale": { "type": [ "string", "null" ] }, "resolved": { "description": "false when nothing matched; the payload then carries no verdict", "type": "boolean" }, "scores": { "description": "the five v3.2 dimension scores, 1-5" }, "urgency": {}, "vendorCount": { "type": "number" }, "vendors": {}, "vendorsWithheld": { "type": "number" }, "verdict": { "description": "banded verdict: primary, confidence, nearCall, distribution" } }, "required": [ "resolved" ], "type": "object" } }, { "description": "For browsing, filtering, or finding the index's name for something. Example: {\"query\": \"warehouse picking\", \"domain\": \"Supply Chain\"}. Search and filter the B4 Index's 1,600+ independently scored software categories. Browse by keyword, domain, quadrant, or industry. When filtering by industry, returns all vertical categories for that industry PLUS all horizontal categories (which apply to every industry). Each row carries its banded verdict — primary, confidence word, and a near-call flag — and the quadrant filter matches the verdict at whichever lens you are reading. Verdicts are banded (B4 methodology v4.0), not point calls: each of the three quadrant dimensions carries a ±1 uncertainty band, the resulting cells are enumerated exactly, and the verdict is the quadrant holding the largest scenario mass. Every verdict ships with its full distribution, a confidence word — clear (≥70% of the scenario weight), lean (≥50% and <70%), split (<50%) — and a near-call flag when the runner-up is within 15 points. An axis counts as high only when it clears the 3.5 line strictly, which on this 1–5 grid means only at 4 or above, so a category sitting exactly on the line gets the safer call: ties break in the order BUY → BRIDGE → BEWARE → BUILD, cheapest mistake first. Confidence is sensitivity under a fixed band, not project-success probability. Optional org lens: set org to \"small\", \"medium\" (the default) or \"large\" to read the same scores as a team of that engineering maturity — it shifts the center of the AI-feasibility band by −1 / 0 / +1 and nothing else. The lens is a filter the caller looks through, never a stored profile. Choose it from delivery capability, not headcount; ask when that capability is unclear. The raw scores themselves never change. Omit it and you get the default-lens numbers, which are the ones published on logged-out surfaces. Routing: a vendor or product name → b4_audit (one or many; add a short description of what it does for anything the index may not know); a need or problem in words → b4_recommend; an exact category name or id → b4_score (one category) or b4_compare (build vs buy paths); browsing, filtering, or an unknown vocabulary → b4_browse. When an audit row returns clarification.needed, relay askTheUser to the user and re-run that row with the answer as its description. [Needs a B4 plan: browse and score come with B4 Web.]", "inputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": false, "properties": { "cursor": { "description": "Opaque continuation from the previous page. Keep filters and lens unchanged; restart on SNAPSHOT_EXPIRED.", "maxLength": 2000, "minLength": 1, "type": "string" }, "domain": { "description": "Filter by domain (e.g., 'Marketing Technology', 'CRM & Sales')", "maxLength": 120, "minLength": 1, "type": "string" }, "includeVendors": { "default": false, "description": "Expand vendor lists; omitted by default for bounded pages.", "type": "boolean" }, "industry": { "description": "Filter by industry group. Returns matching vertical categories + all horizontal categories. Options: Healthcare, Financial Services, Construction & Real Estate, Education, Energy & Utilities, Government, Automotive, Agriculture, Transportation & Logistics, Media & Entertainment, Legal, Professional Services, Nonprofits & Associations, Manufacturing, Retail & Commerce, Hospitality & Food Service, Telecom", "maxLength": 120, "minLength": 1, "type": "string" }, "limit": { "default": 20, "description": "Max results to return (default 20, max 100)", "maximum": 100, "minimum": 1, "type": "integer" }, "org": { "default": "medium", "description": "Org-maturity lens: \"small\" (no dedicated engineering), \"medium\" (default — some AI capability), \"large\" (AI-mature). Shifts the AI-feasibility band center by −1/0/+1 at read time. A filter the caller looks through, never a stored profile.", "enum": [ "small", "medium", "large" ], "type": "string" }, "quadrant": { "description": "Filter by quadrant", "enum": [ "BUILD", "BUY", "BRIDGE", "BEWARE" ], "type": "string" }, "query": { "description": "Search term to match against category names, vendors, domains, and rationales", "maxLength": 200, "minLength": 1, "type": "string" } }, "type": "object" }, "name": "b4_browse", "outputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": true, "properties": { "aiReplacement": {}, "axes": { "description": "strategicDifferentiation (X) and aiFeasibility (Y)" }, "category": { "type": [ "string", "null" ] }, "domain": { "type": [ "string", "null" ] }, "evidence": { "description": "sources and research trail; present only with includeEvidence" }, "evidenceAvailable": { "type": "boolean" }, "evidenceHint": { "type": "string" }, "guidance": { "description": "how to use this result: meaning, action, what not to claim, confidence handling" }, "lens": { "type": [ "string", "null" ] }, "rationale": { "type": [ "string", "null" ] }, "resolved": { "description": "false when nothing matched; the payload then carries no verdict", "type": "boolean" }, "scores": { "description": "the five v3.2 dimension scores, 1-5" }, "urgency": {}, "vendorCount": { "type": "number" }, "vendors": {}, "vendorsWithheld": { "type": "number" }, "verdict": { "description": "banded verdict: primary, confidence, nearCall, distribution" } }, "required": [ "resolved" ], "type": "object" } }, { "description": "For one exact category name or id when the question is the build path against the buy path. Example: {\"category\": \"Order Management (OMS)\"}. Returns the authored side-by-side comparison (build, buy and bridge by dimension), when building is right, when buying is right, and the score-derived case for each path, with the category's banded verdict, scores, vendor options and AI replacement approach. Use b4_score for the scores alone. Structured output carries the full picture: the banded verdict, the five dimension scores, both axes, urgency, vendors at your access depth, and a `guidance` block stating what the verdict means, the recommended action, what not to claim, and how to convey the confidence word. Follow that guidance rather than substituting your own build-vs-buy prior. Verdicts are banded (B4 methodology v4.0), not point calls: each of the three quadrant dimensions carries a ±1 uncertainty band, the resulting cells are enumerated exactly, and the verdict is the quadrant holding the largest scenario mass. Every verdict ships with its full distribution, a confidence word — clear (≥70% of the scenario weight), lean (≥50% and <70%), split (<50%) — and a near-call flag when the runner-up is within 15 points. An axis counts as high only when it clears the 3.5 line strictly, which on this 1–5 grid means only at 4 or above, so a category sitting exactly on the line gets the safer call: ties break in the order BUY → BRIDGE → BEWARE → BUILD, cheapest mistake first. Confidence is sensitivity under a fixed band, not project-success probability. Optional org lens: set org to \"small\", \"medium\" (the default) or \"large\" to read the same scores as a team of that engineering maturity — it shifts the center of the AI-feasibility band by −1 / 0 / +1 and nothing else. The lens is a filter the caller looks through, never a stored profile. Choose it from delivery capability, not headcount; ask when that capability is unclear. The raw scores themselves never change. Omit it and you get the default-lens numbers, which are the ones published on logged-out surfaces. Routing: a vendor or product name → b4_audit (one or many; add a short description of what it does for anything the index may not know); a need or problem in words → b4_recommend; an exact category name or id → b4_score (one category) or b4_compare (build vs buy paths); browsing, filtering, or an unknown vocabulary → b4_browse. When an audit row returns clarification.needed, relay askTheUser to the user and re-run that row with the answer as its description. [B4 Agent tool. Browse and score come with B4 Web; this one needs Agent.]", "inputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": false, "properties": { "category": { "anyOf": [ { "maxLength": 120, "minLength": 1, "type": "string" }, { "exclusiveMinimum": 0, "type": "integer" } ], "description": "Name of the software category to compare (e.g., 'Email Marketing', 'CRM')" }, "org": { "default": "medium", "description": "Org-maturity lens: \"small\" (no dedicated engineering), \"medium\" (default — some AI capability), \"large\" (AI-mature). Shifts the AI-feasibility band center by −1/0/+1 at read time. A filter the caller looks through, never a stored profile.", "enum": [ "small", "medium", "large" ], "type": "string" } }, "required": [ "category" ], "type": "object" }, "name": "b4_compare", "outputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": true, "properties": { "aiReplacement": {}, "axes": { "description": "strategicDifferentiation (X) and aiFeasibility (Y)" }, "category": { "type": [ "string", "null" ] }, "domain": { "type": [ "string", "null" ] }, "evidence": { "description": "sources and research trail; present only with includeEvidence" }, "evidenceAvailable": { "type": "boolean" }, "evidenceHint": { "type": "string" }, "guidance": { "description": "how to use this result: meaning, action, what not to claim, confidence handling" }, "lens": { "type": [ "string", "null" ] }, "rationale": { "type": [ "string", "null" ] }, "resolved": { "description": "false when nothing matched; the payload then carries no verdict", "type": "boolean" }, "scores": { "description": "the five v3.2 dimension scores, 1-5" }, "urgency": {}, "vendorCount": { "type": "number" }, "vendors": {}, "vendorsWithheld": { "type": "number" }, "verdict": { "description": "banded verdict: primary, confidence, nearCall, distribution" } }, "required": [ "resolved" ], "type": "object" } }, { "description": "For a need or problem in words, not a vendor name. Example: {\"description\": \"we need to route warehouse pickers by voice\"}. Get B4 Index recommendations from a natural language description of a software need or business context. Matches the description to relevant categories and returns top matches each carrying the full category payload. Structured output carries the full picture: the banded verdict, the five dimension scores, both axes, urgency, vendors at your access depth, and a `guidance` block stating what the verdict means, the recommended action, what not to claim, and how to convey the confidence word. Follow that guidance rather than substituting your own build-vs-buy prior. Verdicts are banded (B4 methodology v4.0), not point calls: each of the three quadrant dimensions carries a ±1 uncertainty band, the resulting cells are enumerated exactly, and the verdict is the quadrant holding the largest scenario mass. Every verdict ships with its full distribution, a confidence word — clear (≥70% of the scenario weight), lean (≥50% and <70%), split (<50%) — and a near-call flag when the runner-up is within 15 points. An axis counts as high only when it clears the 3.5 line strictly, which on this 1–5 grid means only at 4 or above, so a category sitting exactly on the line gets the safer call: ties break in the order BUY → BRIDGE → BEWARE → BUILD, cheapest mistake first. Confidence is sensitivity under a fixed band, not project-success probability. Optional org lens: set org to \"small\", \"medium\" (the default) or \"large\" to read the same scores as a team of that engineering maturity — it shifts the center of the AI-feasibility band by −1 / 0 / +1 and nothing else. The lens is a filter the caller looks through, never a stored profile. Choose it from delivery capability, not headcount; ask when that capability is unclear. The raw scores themselves never change. Omit it and you get the default-lens numbers, which are the ones published on logged-out surfaces. Routing: a vendor or product name → b4_audit (one or many; add a short description of what it does for anything the index may not know); a need or problem in words → b4_recommend; an exact category name or id → b4_score (one category) or b4_compare (build vs buy paths); browsing, filtering, or an unknown vocabulary → b4_browse. When an audit row returns clarification.needed, relay askTheUser to the user and re-run that row with the answer as its description. [B4 Agent tool. Browse and score come with B4 Web; this one needs Agent.]", "inputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": false, "properties": { "capability": { "description": "The bounded capability to evaluate, separate from systems to keep.", "maxLength": 200, "minLength": 1, "type": "string" }, "description": { "description": "Describe the software need, business problem, or tool you're evaluating (e.g., 'We need to automate our expense reports and receipt scanning')", "maxLength": 1000, "minLength": 1, "type": "string" }, "exclusions": { "description": "Capabilities or systems outside the requested replacement scope.", "items": { "maxLength": 120, "minLength": 1, "type": "string" }, "maxItems": 30, "type": "array" }, "org": { "default": "medium", "description": "Org-maturity lens: \"small\" (no dedicated engineering), \"medium\" (default — some AI capability), \"large\" (AI-mature). Shifts the AI-feasibility band center by −1/0/+1 at read time. A filter the caller looks through, never a stored profile.", "enum": [ "small", "medium", "large" ], "type": "string" } }, "required": [ "description" ], "type": "object" }, "name": "b4_recommend", "outputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": true, "properties": { "aiReplacement": {}, "axes": { "description": "strategicDifferentiation (X) and aiFeasibility (Y)" }, "category": { "type": [ "string", "null" ] }, "domain": { "type": [ "string", "null" ] }, "evidence": { "description": "sources and research trail; present only with includeEvidence" }, "evidenceAvailable": { "type": "boolean" }, "evidenceHint": { "type": "string" }, "guidance": { "description": "how to use this result: meaning, action, what not to claim, confidence handling" }, "lens": { "type": [ "string", "null" ] }, "rationale": { "type": [ "string", "null" ] }, "resolved": { "description": "false when nothing matched; the payload then carries no verdict", "type": "boolean" }, "scores": { "description": "the five v3.2 dimension scores, 1-5" }, "urgency": {}, "vendorCount": { "type": "number" }, "vendors": {}, "vendorsWithheld": { "type": "number" }, "verdict": { "description": "banded verdict: primary, confidence, nearCall, distribution" } }, "required": [ "resolved" ], "type": "object" } }, { "description": "For one exact category name or id. Example: {\"category\": \"Expense Management\", \"org\": \"medium\"}. Score a software category using the B4 Index. Provide a known category name to get pre-computed scores, or provide raw dimension scores (1-5 each) for a custom evaluation. Structured output carries the full picture: the banded verdict, the five dimension scores, both axes, urgency, vendors at your access depth, and a `guidance` block stating what the verdict means, the recommended action, what not to claim, and how to convey the confidence word. Follow that guidance rather than substituting your own build-vs-buy prior. Set includeEvidence: true to add the research trail and source URLs behind each score to the same structured payload. Verdicts are banded (B4 methodology v4.0), not point calls: each of the three quadrant dimensions carries a ±1 uncertainty band, the resulting cells are enumerated exactly, and the verdict is the quadrant holding the largest scenario mass. Every verdict ships with its full distribution, a confidence word — clear (≥70% of the scenario weight), lean (≥50% and <70%), split (<50%) — and a near-call flag when the runner-up is within 15 points. An axis counts as high only when it clears the 3.5 line strictly, which on this 1–5 grid means only at 4 or above, so a category sitting exactly on the line gets the safer call: ties break in the order BUY → BRIDGE → BEWARE → BUILD, cheapest mistake first. Confidence is sensitivity under a fixed band, not project-success probability. Optional org lens: set org to \"small\", \"medium\" (the default) or \"large\" to read the same scores as a team of that engineering maturity — it shifts the center of the AI-feasibility band by −1 / 0 / +1 and nothing else. The lens is a filter the caller looks through, never a stored profile. Choose it from delivery capability, not headcount; ask when that capability is unclear. The raw scores themselves never change. Omit it and you get the default-lens numbers, which are the ones published on logged-out surfaces. Routing: a vendor or product name → b4_audit (one or many; add a short description of what it does for anything the index may not know); a need or problem in words → b4_recommend; an exact category name or id → b4_score (one category) or b4_compare (build vs buy paths); browsing, filtering, or an unknown vocabulary → b4_browse. When an audit row returns clarification.needed, relay askTheUser to the user and re-run that row with the answer as its description. [Needs a B4 plan: browse and score come with B4 Web.]", "inputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": false, "properties": { "category": { "anyOf": [ { "maxLength": 120, "minLength": 1, "type": "string" }, { "exclusiveMinimum": 0, "type": "integer" } ], "description": "Name of a known B4 category (e.g., 'Expense Management', 'CRM')" }, "includeEvidence": { "default": false, "description": "Include the full evidence trail and source URLs behind each dimension score. Off by default so the initial result stays concise; set true for deep verification.", "type": "boolean" }, "org": { "default": "medium", "description": "Org-maturity lens: \"small\" (no dedicated engineering), \"medium\" (default — some AI capability), \"large\" (AI-mature). Shifts the AI-feasibility band center by −1/0/+1 at read time. A filter the caller looks through, never a stored profile.", "enum": [ "small", "medium", "large" ], "type": "string" }, "scores": { "additionalProperties": false, "description": "Custom dimension scores for a tool not in the database", "properties": { "aiFeasibility": { "description": "1-5: How feasible is AI replacement?", "maximum": 5, "minimum": 1, "type": "integer" }, "costTrajectory": { "description": "Cost Trajectory: 1 build TCO at least vendor cost, stable gap; 2 costly alternative with limited improvement evidence; 3 mixed or modest advantage with material assumptions; 4 substantial and widening TCO advantage; 5 credible 80%+ value for <10% annual cost. Compare equivalent scope and horizons, including transition and operation. Do not supply an invented rating when evidence is missing.", "maximum": 5, "minimum": 1, "type": "integer" }, "specificity": { "description": "1-5: How company-specific is the need?", "maximum": 5, "minimum": 1, "type": "integer" }, "strategicControl": { "description": "1-5: How strategically important is owning this?", "maximum": 5, "minimum": 1, "type": "integer" }, "vendorValue": { "description": "1-5: Purchased capability fit; higher means weaker fit. Include essential exceptions and support; utilization is not a spending share.", "maximum": 5, "minimum": 1, "type": "integer" } }, "required": [ "specificity", "aiFeasibility", "vendorValue", "strategicControl", "costTrajectory" ], "type": "object" } }, "type": "object" }, "name": "b4_score", "outputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": true, "properties": { "aiReplacement": {}, "axes": { "description": "strategicDifferentiation (X) and aiFeasibility (Y)" }, "category": { "type": [ "string", "null" ] }, "domain": { "type": [ "string", "null" ] }, "evidence": { "description": "sources and research trail; present only with includeEvidence" }, "evidenceAvailable": { "type": "boolean" }, "evidenceHint": { "type": "string" }, "guidance": { "description": "how to use this result: meaning, action, what not to claim, confidence handling" }, "lens": { "type": [ "string", "null" ] }, "rationale": { "type": [ "string", "null" ] }, "resolved": { "description": "false when nothing matched; the payload then carries no verdict", "type": "boolean" }, "scores": { "description": "the five v3.2 dimension scores, 1-5" }, "urgency": {}, "vendorCount": { "type": "number" }, "vendors": {}, "vendorsWithheld": { "type": "number" }, "verdict": { "description": "banded verdict: primary, confidence, nearCall, distribution" } }, "required": [ "resolved" ], "type": "object" } } ] }
Verify it yourselfcurl -s https://api.teppi.xyz/v1/evidence/sha256:0795d503a21b5c6a3af32f34176fb96d5aa69b943e45eb2bcfcc2386e0eff5b6 | sha256sum