Agent-Skills.md

Agent Skills: Querying Well data

How to query a Well workspace correctly — discover the schema first, then query the right root. Use whenever the user asks about their invoices, companies, contacts, bank transactions, accounts, or accounting ledger in Well, or before writing any well_query_records call.

UncategorizedID: wellapp-ai/well/querying-well-data

Repository

wellapp-ai/well
WellApp-aiLicense: MIT
33550

Install this agent skill to your local

pnpm dlx add-skill https://github.com/WellApp-ai/Well/tree/HEAD/plugins/well/skills/querying-well-data

Skill Files

Browse the full folder contents for querying-well-data.

Download Skill

Loading file tree…

plugins/well/skills/querying-well-data/SKILL.md

Skill Metadata

Name
querying-well-data
Description
How to query a Well workspace correctly — discover the schema first, then query the right root. Use whenever the user asks about their invoices, companies, contacts, bank transactions, accounts, or accounting ledger in Well, or before writing any well_query_records call.

Querying Well data

Well exposes a workspace's financial graph through three MCP tools:

  • well_get_schema() — list every available root (entity type).
  • well_get_schema({ root }) — list the fields available on one root, with types and semantic context.
  • well_query_records({ root, fields, whereClause?, orderBy?, limit? }) — read rows.
  • well_get_entity({ root, id }) — fetch one record by id.

The one rule: discover before you query

Always call well_get_schema(root) first, pick the fields you need from what it returns, then call well_query_records. Field paths are arrays: "invoices.issuer.name" → ["invoices", "issuer", "name"]. Do not guess field names — they vary by root and are documented in the schema response (each field carries a type and often a context explaining what it means).

The roots you can read

Calling well_get_schema() with no argument returns the full set. It includes far more than invoices and companies — in particular the accounting graph:

  • Commercial documents: invoices, invoice_items, invoice_transactions
  • Parties: companies, people, payment_means
  • Banking: accounts, transactions, account_balances
  • Accounting graph (read-only, posted by Well's pipelines): ledger_accounts, journals, journal_entries
  • Reference: tax_rates, exchange_rates, categories, connectors
  • Workspace: memberships, tasks, workspace_connectors

If you are about to answer a financial question by reconstructing it from raw invoices, stop and check well_get_schema() first — the posted ledger (journal_entries, ledger_accounts) is almost always the correct, more accurate source. See the well:compte-de-resultat and well:balance-sheet skills.

Filtering

whereClause is a Hasura-style boolean expression. Use the operator the field's type allows (from the schema):

  • numeric / date → _eq, _gt, _lt, _gte, _lte
  • enum → _eq, _neq, _in, _nin, _is_null
  • text → _eq, _like, _ilike
  • relations → nest: { "issuer": { "name": { "_ilike": "%acme%" } } }

Gotchas

  • Reads are scoped to the authenticated workspace automatically — you never pass a workspace id.
  • Select the specific fields you need (5–15), not everything — it is faster and cheaper.
  • Amounts on commercial documents are in the document currency; check the schema context for currency fields before summing across currencies (see exchange_rates).