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Glama

CDF Finance

by io.github.VessellTech

Parcelas ativas

active_installments
Read-only

Parcelas de compras parceladas (não faturas de cartão — qualquer forma de pagamento com totalInstallments > 1) ainda não pagas. count/total somam TODAS as parcelas em aberto, sem filtro de data — inclui parcelas já vencidas. upcoming traz até 5 parcelas com a data mais próxima, ordenadas de forma crescente; se houver parcela vencida e não paga, ela aparece primeiro (não é só futuro). Use esta ferramenta pra saber o compromisso do usuário com compras parceladas em geral; para o total da fatura mensal de um cartão específico use invoice_for_period, e para faturas de cartão pendentes em geral use list_pending_invoices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNo
countNo
totalNo
upcomingYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and destructiveHint annotations, the description reveals important behavioral details: count/total sum all open installments without date filtering, including overdue ones; upcoming returns at most 5 installments sorted ascending and prioritizes overdue unpaid installments first. This meaningfully informs the agent about edge-case behavior without contradicting any annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence earns its place: it defines the resource, clarifies scoping behavior, explains the upcoming field's ordering, and routes to alternatives. It is front-loaded with the core definition and contains no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters and an output schema exists, the description covers all the behavioral context an agent needs: scope, exclusion of card invoices, aggregation semantics, ordering behavior, and alternative tools. Nothing critical is missing for correct selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and schema coverage is 100% (vacuously). Per the baseline rule, a no-parameter tool receives a 4 since there is no parameter semantics to enhance; the description instead usefully explains response field semantics such as count, total, and upcoming.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource: unpaid installments of installment purchases, explicitly excluding credit card invoices and defining them as any payment method with totalInstallments > 1. It also names the two closest sibling tools (invoice_for_period and list_pending_invoices) and states what this tool is not, making differentiation unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage guidance is explicit: use this tool to understand the user's overall installment purchase commitment. It also provides direct when-not-to-use guidance by pointing to invoice_for_period for a specific card's monthly invoice and list_pending_invoices for pending card invoices generally.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All CDF Finance toolsInspect
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TDQS

A3.7/5.0
Disambiguation3/5

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.

Naming Consistency3/5

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.

Tool Count1/5

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.

Completeness4/5

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.

Resources