update_tagAtualiza nome e/ou cor de uma tag existente do usuário autenticado (id = id da tag). Campos omitidos mantêm o valor atual. count retorna 0 se o id não existir ou não pertencer ao usuário (sem erro).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Id da tag a atualizar | |
| name | No | Novo nome | |
| color | No | Nova cor (ex: hex '#RRGGBB') |
| Name | Required | Description | Default |
|---|---|---|---|
| count | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate mutation (readOnlyHint=false) and non-destructive behavior (destructiveHint=false). The description adds useful behavioral details beyond annotations: omitted fields are preserved, a missing or non-owned id returns count=0 without an error, and the operation is confined to the authenticated user's tags.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the core purpose and then state the two behavioral facts an agent needs: partial update semantics and non-error on missing/non-owned id. No filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple three-parameter update tool, the description, input schema, and output schema together cover the required invocation facts: required id, optional fields, partial-update behavior, authentication scope, and edge-case behavior. Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter is already documented. The description adds semantic value by explaining that id refers to an existing tag owned by the authenticated user, name and color are optional partial-update fields, and an unknown id does not cause an error.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Atualiza' / updates) and clearly identifies the resource: an existing tag belonging to the authenticated user. It names exactly which fields can change (name and/or color) and ties the id parameter to the tag id, distinguishing it from create_tag, delete_tag, and list_tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear operational context: the update is scoped to the authenticated user's tag, and omitted fields keep their current value, implying partial updates. It does not explicitly name alternatives or when-not conditions, but the update-vs-create/delete distinction is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are individually well-described and many cross-reference their closest neighbors, but the set contains several easily confused clusters: create_transaction/confirm_new_transaction, update_equity/add_equity_valuation, the invoice tools (current_invoice, next_invoice, list_pending_invoices, get_invoice), and the many analytics/projection tools. The descriptions help a careful reader, but with 81 tools an agent is likely to misselect among these overlapping surfaces.
CRUD operations consistently use create_/list_/update_/delete_ plus a resource noun, and all names are snake_case. However, there is a large second group of noun-phrase analytics tools (cashflow_forecast, spending_projection, categories_insights, transport_routine) plus one-off verbs such as can_afford, pay_invoice, and validate_current_invoices, so the naming convention is mixed even though it remains readable.
81 tools is far beyond the practical MCP tool surface and exceeds the rubric's 50+ extreme-mismatch threshold. Even if each tool maps to a real finance endpoint, the volume overwhelms an agent's context window and makes selection much harder.
The server covers the finance lifecycle extensively: accounts, cards, invoices, transactions, recurring rules, budgets, goals, debts, equities, categories, tags, cost centers, profile, projections, and insights all have working read/write paths. Minor gaps remain, such as no update/delete for tags and no direct update/delete for system-generated invoices, but agents can usually work around these.