TokenBel Financial Data

trading_stats_get

Read-onlyIdempotent

Get trading statistics for a BCSE exchange-listed share or bond by TokenBel internal identifier (field name: uuid). Use search_by_ticker first. Modes: latest_30d (default, no dates) reads the refreshed 30-day materialized view and includes latest price/yield plus yield_wavg; range (both date_from and date_to, YYYY-MM-DD, inclusive) aggregates raw trade history live and returns yield_min/yield_max only — yield_wavg and all *_latest fields are null in range mode. Omit both dates or provide both; one bound is rejected. Both modes also return daily_series: one point per trade_date (same-day buckets collapsed across market_type/trade_mode/payment_code) with per-day turnover, transactions, price_wavg/min/max, and yield_min/max — no range-level rollup.

Input Schema

TableJSON Schema

Name	Required	Description
`uuid`	Yes	TokenBel internal identifier: opaque hexadecimal string, usually 8 characters such as "78c7e502"; despite uuid field/tool names, it is not an RFC UUID and normally has no hyphens. Listed share or bond id, usually discovered via search_by_ticker.
`date_to`	No	Range end date YYYY-MM-DD (inclusive, >= date_from). Provide both date_from and date_to for range mode; ranges ending today bypass cache.
`date_from`	No	Range start date YYYY-MM-DD (inclusive). Provide both date_from and date_to for range mode; omit both for latest_30d mode.

Output Schema

TableJSON Schema

Name	Required	Description
`mode`	Yes
`uuid`	Yes	TokenBel internal identifier: opaque hexadecimal string, usually 8 characters such as "78c7e502"; despite uuid field names, it is not an RFC UUID and normally has no hyphens.
`period`	Yes
`ticker`	Yes
`price_max`	Yes
`price_min`	Yes
`yield_max`	Yes
`yield_min`	Yes
`price_wavg`	Yes
`yield_wavg`	Yes
`daily_series`	Yes
`trading_days`	Yes
`security_kind`	Yes
`last_trade_date`	Yes
`turnover_amount`	Yes
`price_latest_date`	Yes
`price_wavg_latest`	Yes
`yield_latest_date`	Yes
`yield_wavg_latest`	Yes
`transactions_count`	Yes

TDQS

A4.6/5.0

Behavior5/5

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

The description adds significant behavioral details beyond the annotations (readOnlyHint, idempotentHint): it explains that latest_30d reads a materialized view, range mode aggregates live data, which fields are null in each mode, and the structure of daily_series. No contradictions 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.

Conciseness4/5

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

The description is well-structured and front-loaded with the primary purpose. It is somewhat lengthy but each sentence provides necessary detail. A slight reduction could improve conciseness without losing clarity.

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's complexity (two modes, multiple fields, daily_series), the description covers all key aspects: mode behavior, field availability, uuid clarification, and cache behavior. With an output schema present, the description is complete and sufficient for an agent to use the tool correctly.

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 coverage is 100%, so baseline is 3. The description adds extra meaning: uuid is opaque hex not RFC UUID, dates must be both present or both absent, and ranges ending today bypass cache. This adds value beyond the 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?

The description clearly states the tool gets trading statistics for a BCSE exchange-listed share or bond by a specific identifier (uuid). It distinguishes two modes (latest_30d and range) and explicitly directs users to use search_by_ticker first, making the purpose very clear and distinguishable from sibling tools like token_trading_stats_get.

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?

The description provides clear guidance on when to use each mode: omit both dates for latest_30d, provide both for range, and that one bound is rejected. It also tells users to use search_by_ticker first. However, it does not explicitly compare against sibling tools, which would enhance guidance.

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

All TokenBel Financial Data tools Inspect

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct entity or operation: bonds, shares, tokens, companies, issuers, currency rates, news, and searches. No two tools have overlapping purposes; even similar tools like bond_list and company_bonds_list are clearly differentiated by scope (global vs per-company).

Naming Consistency4/5

Tools mostly follow a pattern of entity_noun + verb (e.g., bond_list, share_get_by_uuid, company_bonds_list). Some exceptions like currency_rate_get and entity_news_list place the verb at the end, but the pattern is predictable and readable.

Tool Count5/5

With 19 tools covering bonds, shares, tokens, companies, issuers, currency rates, news, and trading statistics, the number is well-calibrated to the domain. Each tool serves a clear purpose without redundancy.

Completeness5/5

The tool surface provides comprehensive read access to the financial data domain: search, retrieval, listing with filters, trading statistics, and news. All expected query operations are present, and no obvious gaps are apparent for a data provider.

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