delete_tagExclui uma tag permanentemente (id = id da tag). Não afeta as transações que a usavam além de removê-la delas (relação N:N com cascade). 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 excluir |
| 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?
The description adds meaningful behavior beyond the annotations: deletion is permanent, transactions are only affected by removing the tag reference via N:N cascade, and a non-existent or unauthorized id returns count 0 without error. This directly explains what gets destroyed and how failures behave.
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?
The description is three tight sentences, each adding distinct value: the core action, the cascade effect, and the edge-case behavior. No filler or redundant explanation is present.
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 single-parameter deletion tool with annotations and an output schema, the description covers the essential operating details: permanent deletion, cascading effects, and response behavior for invalid or unauthorized ids. Nothing critical 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% and the sole parameter id is already documented in the schema. The description repeats that id identifies the tag, which adds little beyond what the schema provides, so the baseline score of 3 is appropriate.
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 clearly states a specific action — permanently deleting a tag by its id — and distinguishes this tool from other delete_* siblings by naming the resource and the permanent nature of the operation. It also explains the cascading relationship with transactions, which adds precision beyond the tool name.
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?
The intended use is clear: call this when a tag should be permanently removed. While it does not explicitly name alternatives like update_tag for editing or list_tags for viewing, the context makes the appropriate usage obvious and there are no ambiguous exclusions.
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.