Tesouro em Foco

price_history_ranking

Read-onlyIdempotent

Ranks every bond in the active Tesouro Direto catalog by where its latest published rate sits within its own history — in ONE call. Prefer this for questions like "which bonds have rates near their historical highs?", "how does today's rate compare with the past, across the catalog?", or any cross-bond comparison of rate levels. Do NOT loop price_history_series per paper for that.

For each catalog paper and each requested window it returns rate stats for one side: min/max, nearest-rank percentiles p10/p25/p50/p75/p90 (always actually published rates), last (most recent published rate on or before to) and lastPercentile (0-100: share of the window strictly below last — 92 means the current rate is above 92% of the period, i.e. near the top of its historical range).

Inputs (all optional):

windows: 1-3 of '30d' | '90d' | '1y' | '5y' | 'max', default ['1y']. Ranking is ordered by the FIRST window's lastPercentile (desc); extra windows add context (e.g. ['1y','max']).
side: 'investorBuy' (default — investor PURCHASE rate, STN's Taxa de Compra; the standard quoted rate) or 'investorSell' (sell-back). Only papers currently available for that side are ranked.
productId: filter to one family. Only the seven catalog families are rankable — 'igpm-mais-com-juros-semestrais' has history but no active catalog entries; for it use price_history_series. On 'selic' the percentiles are coarse: the published rate is a spread over the Selic, near zero and rounded to two decimals of a percent, so a window holds few distinct values.
to: anchor date YYYY-MM-DD (default today UTC) — set a past date for "how did the ranking look then?".

Output: ranking[] with productId, maturityDate, year (label year — CONVERSION year for renda-mais/educa-mais) and per-window stats; meta.missing lists catalog papers with no data in any window (e.g. just launched).

Caveats: this is a statistical description of published rates, NOT investment advice, a return forecast, or a recommendation — never present the ranking as "best bonds to buy". lastPercentile compares each paper against ITS OWN history only; a high percentile means the rate is high relative to that paper's past, nothing more. Comparing entries across families is meaningful only in that relative sense (a prefixado percentile reflects nominal rates; an ipca-mais percentile reflects real rates).

Rates are decimal fraction strings (same as price_history_series, simulate_bond, live_quotes_lookup).

Input Schema

TableJSON Schema

Name	Required	Description
`to`	No	Anchor date YYYY-MM-DD for all windows (inclusive end). Default: today (UTC). Set a past date to ask 'how did the ranking look on that day?'.
`side`	No	Which rate to rank: 'investorBuy' (default — the rate at which the investor buys from the Treasury, the standard quoted rate) or 'investorSell' (sell-back rate).
`windows`	No	Lookback windows ending at `to` (1-3, default ['1y']): '30d' \| '90d' \| '1y' \| '5y' \| 'max' (full history). The ranking is ordered by the FIRST window; extra windows add context (e.g. ['1y','max']).
`productId`	No	Optional filter to a single product family. Omit to rank the whole active catalog. Only catalog families are rankable (no 'igpm-mais-com-juros-semestrais' — it has history but no active catalog entries).

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 6, 2026

changedInput schema / properties / productId / description

Previous value: -"Optional filter to a single product family. Omit to rank the whole active catalog. Only catalog families are rankable (no 'selic' / 'igpm-mais-com-juros-semestrais' — those have history but no active catalog entries)."New value: +"Optional filter to a single product family. Omit to rank the whole active catalog. Only catalog families are rankable (no 'igpm-mais-com-juros-semestrais' — it has history but no active catalog entries)."

changedInput schema / properties / productId / enum

Previous value: -[
-  "prefixado",
-  "prefixado-com-juros-semestrais",
-  "ipca-mais",
-  "ipca-mais-com-juros-semestrais",
-  "renda-mais",
-  "educa-mais"
-]New value: +[
+  "prefixado",
+  "prefixado-com-juros-semestrais",
+  "ipca-mais",
+  "ipca-mais-com-juros-semestrais",
+  "renda-mais",
+  "educa-mais",
+  "selic"
+]

AddedJul 2, 2026

TDQS

A5/5.0

Behavior5/5

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

Annotations already mark read-only/idempotent, and the description adds meaningful behavioral detail well beyond that: percentiles are always actually published rates, lastPercentile is the share strictly below last, ranking is ordered by the first window, papers unavailable for the selected side are excluded, and the selic granularity caveat is disclosed. No contradiction with annotations.

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 long but densely informative with no filler. It is front-loaded with purpose and usage, then parameter semantics, then caveats and output format notes, making it easy to scan. Every sentence contributes to correct selection or invocation.

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?

For a complex ranking tool, it covers all relevant aspects: defaults, ordering, side availability, missing data via meta.missing, decimal string format, and important caveats about not presenting ranking as advice. The output schema exists, so return-value explanation is unnecessary, and the description still summarizes key output semantics.

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

Parameters5/5

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

Schema coverage is 100%, yet the description adds significant meaning: windows ordering semantics, investorBuy meaning 'STN's Taxa de Compra', productId restricting to rankable families only, and `to` as an inclusive anchor for historical looks. Each parameter's behavior is fully elaborated beyond the raw schema.

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?

Description opens with a specific verb-resource pair: 'Ranks every bond in the active Tesouro Direto catalog by where its latest published rate sits within its own history — in ONE call.' It also explicitly contrasts with price_history_series, so the agent can distinguish this tool without opening other definitions.

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?

Provides explicit when-to-use scenarios with example questions and a direct exclusion: 'Do NOT loop price_history_series per paper for that.' Also routes igpm-mais-com-juros-semestrais users to price_history_series, leaving no ambiguity about alternatives.

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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