brazil-macro-ai

get_brazil_copom_path

Returns market-implied Brazilian Selic expectations for upcoming Copom meetings, derived from B3 DI1 futures via a meeting-step bootstrap (method_id copom_path_di1_v1). Each entry gives the implied Selic level and the implied change in basis points for that specific meeting date — not rounded to 25bp increments.

Use when: estimating expected BCB policy changes, the terminal rate, or
cumulative easing/tightening priced by the market over the next 1-8
Copom meetings.
Do not use when: you want economists' survey expectations instead of
market pricing (use brazil_focus_revisions) or a direct comparison
between the two (use compare_brazil_market_vs_focus).
Limitations: requires liquid DI1 data for the as_of date's most recent
trading day; DU counts use the validated B3 trading calendar (A6.1).

Args:
    as_of: optional YYYY-MM-DD date. Defaults to today.
    meetings: number of upcoming Copom meetings to return (1-8, default 4).
    agent_id, session_id, discovery_source: optional C1 telemetry fields.
    payment_token: required in staging for this priced capability
        ($0.10/call per pricing.yaml) — omit to get the simulated
        payment_required response instead of a result.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`as_of`	No
`agent_id`	No
`meetings`	No
`session_id`	No
`payment_token`	No
`discovery_source`	No
`synthetic_identity`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 14, 2026

TDQS

A4.9/5.0

Behavior5/5

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

With no annotations, the description carries the full behavioral burden, and it does: it discloses the bootstrap source, the unrounded output trait, data-liquidity precondition, calendar validation, and the staged payment behavior (payment_token omission returns simulated payment_required). This is substantive behavioral context, not just a restatement of the tool's name.

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 organized into tight, label-led sections (purpose, use when, do not use, limitations, args) and front-loads the core result and method before routing to alternatives. Each sentence adds distinct information without boilerplate.

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?

The output schema exists, so return-value details are not required in prose. The description provides use-case context, exclusions, limitations, and payment behavior needed to invoke the tool, and the only minor gap (synthetic_identity) does not prevent correct default use. Overall it is complete for a 7-parameter tool with zero annotations.

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?

Schema description coverage is 0%, so the prose must supply parameter meaning; it clearly explains as_of, meetings, telemetry fields, and payment_token, including defaults, ranges, and staging behavior. However, synthetic_identity is omitted from the Args section and has no schema description, so one of seven parameters is left unexplained.

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 names a specific verb and resource: returns market-implied Selic expectations for upcoming Copom meetings, with a derived methodology and exact unit (implied level and bp change, unrounded). It distinguishes itself from survey-based siblings by emphasizing 'market-implied' and by naming alternatives in the usage section.

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?

Explicit 'Use when' lists the intended analytical cases (expected BCB changes, terminal rate, cumulative easing/tightening), and 'Do not use when' names alternatives brazil_focus_revisions and compare_brazil_market_vs_focus. Additions like liquid-data and trading-calendar limitations orient the agent about validity conditions.

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

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