tw-market-data

Read the macro regime

macro_regime_read

Read-onlyIdempotent

總經 Regime:景氣信號、利率與殖利率曲線、匯率、資金流。

    ★ 這支講的是**整個市場**,不是任何一檔個股 —— 所以它不收 ticker。
    ★ 事實整理,不是投資建議、不是預測。輸出帶 `does_not_prove`。
    ★ ⚠️ `macro_worldbank` 類的來源會**回溯修訂**歷史年度:今天讀到的舊年度數字
      和當時看到的不是同一個,`pit_notes` 會標出來。
    ★ Args:只有 `as_of`(選填)—— 它**不收 ticker**,因為主體是整個市場。
    ★ Returns:同一個誠實信封;`subject` 固定是 "TW_MARKET"。
    ★ 例如問「現在景氣循環在哪個位置」就是這一支,而不是問某一檔。
    ★ PRECONDITIONS:自己取數;requires 一個已識別的 session。
    ★ SIDE EFFECTS:read-only,does not 寫入。

Input Schema

TableJSON Schema

Name	Required	Description	Default
`as_of`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4/5.0

Behavior4/5

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

Annotations already carry readOnlyHint=true, idempotentHint=true, destructiveHint=false, and the description aligns (read-only, does not write). Beyond annotations it adds genuine value: the output is fact-collection not advice/prediction and carries does_not_prove; WorldBank-type sources get retroactively revised so historic-year numbers differ from what was seen before, flagged via pit_notes; subject is fixed to TW_MARKET. The retroactive-revision disclosure is substantial behavioral context. 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.

Conciseness3/5

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

Front-loaded with the core purpose and organized with ★ bullets, but verbose: the fact that it does not take a ticker is repeated three times ('所以它不收 ticker', '它不收 ticker 因為主體是整個市場', '不收 ticker'). Several lines re-state what the schema and annotations already convey (single optional arg; read-only), adding length without new information.

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

Completeness4/5

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

Thorough for a simple read tool: an output schema exists so return format is covered externally, and the description covers the subject scope (market vs ticker), the honesty wrapper (does_not_prove), the point-in-time revision caveat, preconditions (identified session), and side effects. Only minor gap is as_of semantics, mentioned under parameter scoring.

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

Parameters3/5

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

Schema coverage is 0% so the description carries the burden. It correctly states the only argument is as_of (optional) and that it does not take a ticker. However, it never explains what as_of actually controls (e.g., the point-in-time date for which regime state is read) or any date format semantics. This partial compensation earns a 3, not higher.

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?

States specific verb+resource: reads the 總經 (macro) regime — business cycle signals, rates, yield curve, FX, capital flows. Explicitly distinguishes itself from single-stock tools ('這支講的是整個市場,不是任何一檔個股'), scoping the tool precisely. The example question ('現在景氣循環在哪個位置' is this tool) anchors the purpose concretely.

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

Usage Guidelines4/5

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

Gives a clear usage context: use when asking about the market-level business cycle, not about an individual ticker. States it does NOT take a ticker and is not for single-stock questions. Does not explicitly name sibling alternatives like query_regime or positioning_read as the alternative route, so the exclusion is implied rather than named.

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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TDQS

A4/5.0

Disambiguation4/5

The tools are largely distinct: querying, searching, backtesting, risk reads, alerts, memory, and audit functions each have clear homes. A few adjacent pairs (risk_read vs risk_assess, company_health_check vs positioning_read) could be confused, but the descriptions draw explicit boundaries.

Naming Consistency3/5

There are strong consistent clusters like list_*, get_*, run_*, and memory_*, but the *_read suffix alternates with noun-first names like company_health_check, and bare-verb tools like ask, calendar, chart, and screen break the pattern. The naming is readable but not uniform.

Tool Count2/5

Forty tools is well past the 25+ threshold and makes the surface heavy for an agent to navigate, even though the breadth reflects a genuinely wide platform. Several clusters could plausibly be consolidated without losing capability.

Completeness4/5

The tool surface covers the main lifecycle well: discovery, point-in-time querying, filings search and full text, backtesting, research, risk assessment, alerts, memory, approvals, and provenance verification. Minor gaps exist—no strategy management tools, no memory deletion, no bulk export—but agents can work around them.

Resources

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