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PopNx MCPMCP servers for people who use AI · explained in plain words

dVeracity Semantic API

by d-veracityversion 0.8.3i★ 0iComputer or cloud
Registry namecom.dveracity/semantic-mcp

How to install

What it does

Validate emissions data against Open Footprint, check EU CBAM records, query verified methane data

  • Connects Computer or cloud
  • Account or key Cloud: No key needed · Local: Needs DVERACITY_API_KEY
  • Category Other

Install

Pick the AI app you use, then copy the settings.

Passed 5/5 checks · What you ask goes through the maker’s server (api.dveracity.com) · ✓ Commands checked Nov 14, 2026

First: which AI do you use?

Pick your app and the steps appear below.

Works with Claude · about 2 min

No key, nothing to install · Set it up once on claude.ai or the desktop app, then use it in chat · free accounts can add 1 · on Team/Enterprise an Owner adds it

  1. Open Claude’s Connectors page

    CustomizeConnectors

    CustomizeConnectors1Add2https://…3Add4
  2. Click “Add” → “Custom” → “Web” and fill in these 2 fields

    Copy each value into the field with the same name in Claude, then click Continue

    Name · NamedVeracity Semantic API
    Remote MCP server URL · Addresshttps://api.dveracity.com/mcp

    Click Continue past the sign-in settings Claude detected · under Authentication choose what the maker says (Sign in now, Sign in when needed or No sign in), then click Add

  3. Turn it on in a chat

    +ConnectorsdVeracity Semantic API

  4. Try it

    Use dVeracity Semantic API and tell me what you can do for me, then show me one thing

    ✓ If Claude says it is using dVeracity Semantic API or shows a dVeracity Semantic API tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with ChatGPT, depending on your plan

Full MCP: ChatGPT Business, Enterprise or Edu on the web · Pro: connects with read/fetch permissions, so tools that change data may not work · Plus: not confirmed in OpenAI’s docs; if you see an add-custom-MCP option on the Plugins page you can try these steps · web only

  1. Open ChatGPT’s add-MCP page on the web

    Plugins+Add custom MCP server

    ChatGPTPlugins1+2https://…3Create4
  2. Fill in the name and address

    Enter a name, paste the address under Connection, tick the risk warning and click Create as a plugin

    Name · NamedVeracity Semantic API
    Connection · Addresshttps://api.dveracity.com/mcp
  3. Pick dVeracity Semantic API in a chat

    Start a new chat and pick dVeracity Semantic API from your plugins before typing

  4. Try it

    Use dVeracity Semantic API and tell me what you can do for me, then show me one thing

    ✓ If ChatGPT says it is using dVeracity Semantic API or shows a dVeracity Semantic API tool in the answer, you are connected

Menu names checked against OpenAI’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Claude Code · about 2 min

No key, nothing to install

  1. Open Terminal

    Mac: press Command+Space and type Terminal · Windows: open PowerShell

  2. Paste this command and press Enter

    claude mcp add --transport http --scope user semantic https://api.dveracity.com/mcp
  3. Type /mcp in Claude Code

    You should see dVeracity Semantic API listed as connected

  4. Try it

    Use dVeracity Semantic API and tell me what you can do for me, then show me one thing

    ✓ If Claude Code says it is using dVeracity Semantic API or shows a dVeracity Semantic API tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Cursor · about 2 min

No key, nothing to install

  1. Click this button to open Cursor

    Open in Cursor

    Cursor asks you to confirm; click Install

  2. Open the AI chat in Cursor in Agent mode

  3. Try it

    Use dVeracity Semantic API and tell me what you can do for me, then show me one thing

    ✓ If Cursor says it is using dVeracity Semantic API or shows a dVeracity Semantic API tool in the answer, you are connected

Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with VS Code · about 2 min

No key, nothing to install

  1. Click this button to open VS Code

    Open in VS Code

    VS Code asks you to confirm; click Install

  2. Open the AI chat in VS Code in Agent mode

  3. Try it

    Use dVeracity Semantic API and tell me what you can do for me, then show me one thing

    ✓ If VS Code says it is using dVeracity Semantic API or shows a dVeracity Semantic API tool in the answer, you are connected

Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.

See every app that uses MCP →

Address for apps that connect over the web

Addresshttps://api.dveracity.com/mcp

JSON settings are under “For developers” below

Stuck? Ask people who use dVeracity Semantic API💬 Discussion →
For developers: Terminal commands and JSON settings

Over the web

Claude Code

claude mcp add --transport http --scope user semantic https://api.dveracity.com/mcp

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "semantic": {
      "url": "https://api.dveracity.com/mcp"
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "semantic": {
      "type": "http",
      "url": "https://api.dveracity.com/mcp"
    }
  }
}

Installed on your computer

Claude Code

claude mcp add --scope user semantic --env DVERACITY_API_KEY=your-value -- npx -y @dveracity/semantic-mcp

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "semantic": {
      "command": "npx",
      "args": [
        "-y",
        "@dveracity/semantic-mcp"
      ],
      "env": {
        "DVERACITY_API_KEY": "your-value"
      }
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "semantic": {
      "command": "npx",
      "args": [
        "-y",
        "@dveracity/semantic-mcp"
      ],
      "env": {
        "DVERACITY_API_KEY": "your-value"
      }
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "semantic": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@dveracity/semantic-mcp"
      ],
      "env": {
        "DVERACITY_API_KEY": "your-value"
      }
    }
  }
}

Values you fill in

  • DVERACITY_API_KEY secret required env
    dVeracity API key (dvrc_...). Required for the stdio package; metered calls are billed to it. Not used by the remote endpoint, which authenticates with OAuth.
  • DVERACITY_API_URL env
    Optional. Override the API base URL; defaults to production.
  • DVERACITY_KERI_AID env
    Optional. Agent AID enabling vLEI-verified identity mode.
  • DVERACITY_KERI_PRESENTATION env
    Optional. Path to the CESR presentation used with the agent AID.

Descriptions are as written by the maker.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

At a glance

Downloads per weeki
443/wk
Verified domain
✓ dveracity.com
Licencei
Apache-2.0
Connection
Computer or cloud
Transport
stdio, streamable-http
Latest versioni
0.8.3
Categoryi
Other
Published to registryi
Nov 3, 2026
Code last changedi
Nov 3, 2026
Maker
d-veracity
Packages
npm: @dveracity/semantic-mcp
Registry status
Active

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Connect over the internet in

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

Run on your computer in

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

All apps, with pros and cons →

Related guides

What it can do

Tool names and descriptions exactly as the server reported them on Nov 11, 2026. The maker wrote them, not us; we show them as plain text.

  • semantic_query

    Use this when a user asks a specific question about verified oil-and-gas emissions data, for example methane emissions for a site, company or period (PPDM, OGMP 2.0). Call semantic_templates first to see what the data can answer. Do not use for general climate questions. On payme

  • semantic_templates

    Use this when you want to see which kinds of questions the verified emissions data can answer, before calling semantic_query.

  • credits_balance

    Deprecated: use billing_status, which also shows plan and free allowance. Removal planned for 0.9.

  • list_standards

    Use this when you need to see which sustainability data standards and versions validate_data can check, before calling it.

  • validate_data

    Use this when a user wants a payload checked against a standard other than Open Footprint; call list_standards first to see which are supported. For Open Footprint payloads use ofp_validate. Only masterData or referenceData; call list_standards first.

  • keri_identity

    Use this when an organisation needs to confirm which verified legal entity and agent identity dVeracity is attributing calls to. Only relevant when vLEI identity is configured.

  • ofp_models

    Use this when a user is building an app, database or integration on the Open Footprint standard and needs to know what the model covers. Start here before any other ofp_ tool. The response summary carries the served counts.

  • ofp_search_entities

    Use this when you need the Open Footprint entity for a concept such as "Scope 3 emissions", "facility" or "product footprint". Do not use for emission factors or calculations. Matches entity names, descriptions and field names; use ofp_entity for the full definition.

  • ofp_entity

    Use this when you need one entity's fields, types, keys and relationships, for example to design a table or an API payload. Pass domain when known: ambiguous names fail rather than guessing (ofp_models reports ambiguousNameCount).

  • ofp_sectors

    Use this when a user asks which industries Open Footprint covers or whether a sector has a reference implementation. implemented means a reference implementation exists; planned or placeholder means nothing is published.

  • ofp_sector

    Use this when you need one sector's classification, status and reference artifacts.

  • ofp_policies

    Use this when a user asks which validation rules apply to a sector's emissions records. Do not use for regulations; use compliance_policies. inputs lists the e-ledger fields each policy reads (e.g. co2e_kg, direction), not canonical Open Footprint names. published:false means no

  • compliance_policies

    Use this when a user needs data checked against a regulation, for example EU CBAM, to find the approved policy to run. Do not use for Open Footprint sector rules; use ofp_policies. Returns only APPROVED policies; drafts and rejected never appear. An empty list means none publishe

  • compliance_policy

    Use this when you need the full rules, provenance and coverage of one approved regulatory policy. Returns Rego only when the source was retained; otherwise rego_unavailable: source_not_retained. A policy without Rego is not loaded into the engine; enforcement says whether its str

  • compliance_evaluate

    Use this when a user wants an import record or an annual EU CBAM declaration (Reg. (EU) 2023/956) checked against an approved policy before filing. Do not use for carbon-footprint calculations or for regulations compliance_policies does not list. Runs the policy's regulation-deri

  • compliance_evaluation

    Use this when a user wants to retrieve or audit a previous regulatory evaluation by its id. Only the caller who ran it can read it; another account's id answers not found. Requires compliance:read.

  • compliance_policy_register

    Use this when a user asks which provisions of a regulation an evaluation actually checks and which it does not. Shows which provisions are encoded and which are not: a pass on the encoded checks is not compliance with excluded provisions. Requires the compliance:read scope.

  • ofp_validate

    Use this when a user wants an emissions or footprint record (JSON) checked against the Open Footprint model or a sector's guardrails before storing, exchanging or reporting it. Do not use for general data-quality questions without a payload. Checks structure, declared constraints

  • ofp_semantics

    Use this when mapping fields from SAP, another ERP or a supplier feed onto Open Footprint. A high fieldCount is a generic fallback; pass maxFieldCount (10 is a good start) for codes specific enough to align on.

  • ofp_semantic_code

    Use this when you have a source-system field and need to find where it belongs in the Open Footprint model. Codes carried by more than ten fields are generic classifications; aligning to one asserts less than it appears.

  • ofp_model_provenance

    Use this when a user asks which version of the Open Footprint standard they are designing against.

  • billing_plans

    Use this when you need to know what each dVeracity plan includes or what the free allowance covers. Show dVeracity plans, what each plan includes and the free-tier allowance.

  • billing_status

    Use this when a call was refused for credits or plan, to tell the user exactly what is missing. Use it after a 402 to tell your human exactly what is missing.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 14, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified against the domain dveracity.com (the registry checks domain ownership)

  • ✓ Pass

    Still maintained

    Code last changed 11 days ago

  • ✓ Pass

    Has a licence

    Uses Apache-2.0

  • ✓ Pass

    Endpoint responds

    Responded in 612 ms (HTTP 200)

  • – Not applicable

    Sign-in with OAuth

    No sign-in needed

  • ✓ Pass

    No hidden instructions in tool descriptions

    Read 23 tool descriptions and found no hidden instructions to the AI

Discussion

Ask, share a tip or report that it does not work. Sorted by what people marked helpful.

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User reviews

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Compared with others in Otheri

  • More stars than 0% of the other 19754 servers in this category
  • Published to the registry more recently than 79% of the other 19754 servers in this category
  • Basic checks equal to or better than 100% of the other 19754 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is dVeracity Semantic API safe?

It passed 5 of 5 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: DVERACITY_API_KEY

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed 11 days ago, and the latest version (0.8.3) reached the registry 11 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT on the web (full MCP on Business and above; Pro read-only).

What can I use instead?

In the same category: World Monitor, Claude Flow, Windmill

Others in the same category

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

World Monitor

Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 97 tools.

by koala73Widely used★ 90.6KUpdated yesterday

Runs in the cloud✓ service owner · worldmonitor.app

Claude Flow

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

by ruvnetWidely used↓ 13.5K/wk★ 81.7KUpdated 14 months ago

Runs on your computer

Windmill

Run Windmill scripts and flows and manage jobs, schedules, resources and variables.

by windmill-labsWidely used★ 18.6KUpdated 2 days ago

Runs in the cloud

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

dVeracity Semantic MCP server

Gives any MCP-capable AI agent (Claude Code, Cursor, custom agents) metered access to the dVeracity Semantic API — natural-language queries over the verified-emissions knowledge graph (Open Footprint / PPDM / OGMP-methane) — and VaaS standards validation.

Prerequisites

  1. A free Explorer account (OAuth) or a paid plan: https://dveracity.com/pricing — Explorer includes API-key management and a monthly metered-call allowance.
  2. An API key (dvrc_…): POST /api/v1/api-keys (or the dashboard)
  3. API credits for calls beyond the free allowance: POST /api/v1/vaas/credits/purchase (or ask the agent to use billing_purchase)

The machine-readable service contract lives at GET /api/v1/semantic/manifest (public, no auth).

Install

From this directory: npm install

Claude Code
claude mcp add dveracity \

-e DVERACITY_API_KEY=dvrc_yourkey \ -- node /path/to/dVE/mcp/semantic-mcp/index.js

Generic MCP JSON config (Cursor, etc.)
{

"mcpServers": { "dveracity": { "command": "node", "args": ["/path/to/dVE/mcp/semantic-mcp/index.js"], "env": { "DVERACITY_API_KEY": "dvrc_yourkey" } } } }

Optional: DVERACITY_API_URL overrides the API base URL (defaults to prod).

KERI mode — verified agent identity (optional)

If the agent holds a dVeracity Agent Authorization credential (an ACDC issued by its Legal Entity, chained to the Legal Entity's vLEI — see elm/docs/VLEI_AGENT_TOKENS_DESIGN.md), set:

DVERACITY_KERI_AID=<the agent's AID (credential issuee)>

DVERACITY_KERI_PRESENTATION=/path/to/agent-credential.cesr # self-contained CESR

The server then authenticates the agent by verifiable presentation (challenge → exchange → 1-hour session, refreshed transparently) and attaches X-Keri-Session to every call: the API key keeps carrying billing, the KERI session adds verified identity — every metered call is attributed to the agent AID and Legal Entity LEI in dVeracity's audit trail. The keri_identity tool (free) shows the active identity. Scope denials (a credential that doesn't carry e.g. semantic:query) surface as actionable errors naming the carried scopes. Signify-based nonce signing is a planned enhancement.

Tools

ToolCostWhat it does
semantic_querycreditsNatural-language question over the verified-emissions knowledge graph
semantic_templatesfreeCatalog of supported query templates
credits_balancefreeRemaining credit balance
list_standardsfreeStandards VaaS can validate against
validate_datacreditsValidate a payload against a supported standard
keri_identityfreeThis agent's verified vLEI identity, when KERI mode is configured

Every tool definition carries _meta.pricing: { "unit": "credit", "amount": , "usd": }, with amount 0 for a free tool. A plan-gated tool also carries "plan_required": " " — 0 credits on compliance_policies or compliance_evaluate means "included in the VaaS plan", not "free for any account".

Billing
ToolCostWhat it does
billing_plansfreePlans, credit packs, per-credit price and the free allowance (anonymous on the hosted endpoint)
billing_statusfreeThis account's plan, balance and remaining free allowance
billing_purchasefreeOne-time credit checkout: returns a checkoutUrl for a human, plus a paymentLink when the deployment configures one
billing_subscribefreeMembership checkout: returns checkoutUrl only; recurring charges need human approval
Open Footprint canonical model

Design-time tools for building an application on the Open Footprint standard. Reading the model is free; only the check at the end is metered.

ToolCostWhat it does
ofp_modelsfreeThe model domains (nine as of openfootprint b60a24e), and which database dialects have published DDL
ofp_search_entitiesfreeSearch the canonical entities (262 entries as of b60a24e) by name, description or field
ofp_entityfreeOne entity in full: fields, types, keys, relationships, physical table
ofp_sectorsfreeIndustry sectors, each with a status
ofp_sectorfreeOne sector, with its reference artifacts
ofp_policiesfreeA sector's Rego guardrails, or an explicit "none published"
compliance_policiespaid planApproved regulatory compliance policies (rules extracted from a regulation, admin-approved); never drafts
compliance_policypaid planOne approved policy: Rego, extracted rules, inputs, provenance
compliance_policy_registerpaid planThe published release register: every provision, its legal reference, review status and why it is or is not enforced
compliance_evaluatepaid planExecute one named approved policy against a record: four-valued decision, per-check results, missing inputs, remediation, coverage. Stores an audit record
compliance_evaluationpaid planRead back one stored evaluation — the caller's own only
ofp_validatecreditsCheck a payload against the model and, optionally, sector guardrails
ofp_semanticsfreeO-DEF semantic codes, for aligning another system's fields onto the model
ofp_semantic_codefreeWhich canonical fields carry one code — the reverse lookup a connector needs
ofp_model_provenancefreeWhich snapshot of the standard this deployment serves

Two behaviours are deliberate and worth knowing before you build against them.

Ambiguous entity names fail rather than resolve. dozens of entity names (the ofp_models summary reports the count as ambiguousNameCount) are defined in more than one domain — Country is in four. ofp_entity without a domain returns an error listing the candidates instead of picking one. Pass domain whenever you know it.

Semantic codes vary in usefulness. Most canonical fields carry an O-DEF code, but a code shared by many fields is a generic classification, and aligning to one asserts almost nothing. The ofp_models summary reports the real shape under precision — preciseFieldThreshold (the fieldCount at or below which a code is precise rather than generic), fieldsOnPreciseCodes and preciseShareOfAnnotated — and those follow the vendored snapshot rather than this document. Every code is returned with its fieldCount: check it before aligning to one, and pass maxFieldCount at that threshold to ofp_semantics to see only the precise ones.

"Nothing published" is an answer, not an error. Most sectors are named in the taxonomy but have no reference implementation, and only seven publish policy guardrails. ofp_policies on such a sector returns published: false with a reason, and ofp_validate reports policy.ran: false. Both mean *no rules are published*, never *there are no constraints* — a payload checked for structure alone is not a compliant one, and should not be described as one.

A fourth outcome, unevaluable, means the sector's rules ran but every rule that came back false reads an input the payload does not carry (policy.missingInputs, e.g. co2e_kg, direction, counterparty_industry). Those are e-ledger record fields, not canonical Open Footprint field names — ofp_policies lists them per policy under inputs. Unevaluable is neither a pass nor a breach, and valid is null.

What ofp_validate checks, and what it does not

The response is a contract, not a verdict. Every call reports the check catalogue in two lists: checked (what ran) and checks_not_run (what did not, each with a reason and usually a detail). Read both before describing a payload as anything.

CheckStatusReason reported when it does not run
schema — presence, primary key, types, declared constraintsrunsentity_has_no_fields
value_rangeruns where the model declares a bound: a quantity outside the declared minimum or maximum is rejected. Which fields declare a bound moves with the vendored snapshot, so it fires on some entities and not others — read checked and schema.coverage.constraintsDeclared per callno_range_declared, no_numeric_fields
unit_coherencenot runnot_implemented
calculation_reproducibilityruns where the record carries all three of a quantity, an emission factor value and a stated CO2e result: quantity × factor = result is reproduced within 1%, and a record that contradicts itself is rejectedno_calculation_inputs, calculation_inputs_incomplete, ambiguous_calculation_inputs, calculation_inputs_unparseable
temporal_consistencyruns: a validity period whose end precedes its start is rejectedno_validity_pair, validity_pair_incomplete, validity_values_unparseable
enum_membershipruns where the vocabulary publishes its members: a well-formed key for a referent that does not exist is rejectedno_members_published, no_reference_field_supplied, reference_ids_unparseable
referential_integritynot run: keys are pattern- and member-checked, never resolved against live recordsno_data_plane
factor_provenancenot runnot_implemented
materialitynot runnot_implemented
sector_policyruns when a sector with published guardrails covers the record typeno_sector_supplied, no_policy_published, policy_source_missing, policy_package_unparseable, not_applicable, unevaluable

Any check can also report schema_not_run, which means the structural check it builds on could not run at all.

calculation_reproducibility is self-referential and nothing more. It resolves its three inputs from the model — the field carrying the emission-measure role, a … Factor Value (never a … Factor ID, which is a reference to a factor rather than a number to multiply by) and a … CO2e … result — or, for a record in the vocabulary the guardrails read, from quantity_value / emission_factor_value / co2e_kg. A slot the record fills more than once is ambiguous_calculation_inputs and the check declines rather than picks. The 1% tolerance is the one CalculationAccuracy in the verification engine and calc_tolerance in the ISO 14064 quantification policy use, so the identity has one tolerance on every surface. What it catches is a record whose own numbers do not multiply out. It does not say the factor is the right one for this source and period (factor_provenance, still not run) or that the quantity came from the meter it claims (the data plane, still not run) — a reproduced calculation is a self-consistent record, not a verified one.

  • schemaValid is the structural verdict (null if the structural check could not run).
  • assuranceLevel names the depth earned: schema-only, schema-and-value, schema-value-and-policy or full. Each level needs every check beneath it, so guardrails without a value check is still schema-only. The ladder is gated on value_range — a bound the model itself declares — so a record that reproduced its own arithmetic without one still reads schema-only; checked is where that shows up, and it is the more precise of the two.
  • Every violation and warning carries severity (error | warning). Rule ids are stable: required_field_missing, pattern_mismatch, format_mismatch, type_mismatch, primary_key_missing, enum_violation, value_range (with bound: minimum | maximum), temporal_consistency, enum_membership, calculation_reproducibility (with expected, received, tolerance and the three inputs it read), … unknown_field is a per-field warning and stays one.
  • unknown_field w

Only the beginning is shown; read the rest in the repo