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ahmthamza
by ahmthamza

evds_get_data

Fetch Turkish EVDS financial series with custom date range, frequency, aggregation, and formula, and preview output in chat.

Instructions

Fetch one or more EVDS series with full API features and preview in chat.

Args: series: EVDS series codes, e.g. ['TP.DK.USD.A.YTL', 'TP.FG.J0']. start: Start date (dd-mm-yyyy or yyyy-mm-dd). end: End date (defaults to start). frequency: Target frequency: gunluk/isgunu/haftalik/ayda2/aylik/ ceyreklik/altiaylik/yillik (or codes 1-8). Empty = series default. aggregation: How to aggregate when reducing frequency: avg, min, max, first, last, sum. formula: Transformation: duzey, yuzde_degisim, fark, yillik_yuzde, yillik_fark, yilsonu_yuzde, yilsonu_fark, hareketli_ortalama, hareketli_toplam (or codes 0-8). Empty = level. max_rows: Rows in the preview (default 50).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
startYes
seriesYes
formulaNo
max_rowsNo
frequencyNo
aggregationNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses meaningful behavior: date defaults (end defaults to start), frequency and formula numeric codes, preview row counts, and aggregation semantics. Missing are authentication/network requirements and error behavior, but the core side effects and preview behavior are covered.

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 front-loaded with a one-sentence summary, then uses a compact Args block. Each parameter line is dense with useful details and no filler. For seven parameters, the length is justified and well structured.

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?

Given the tool's complexity (7 parameters, transformations, aggregation), the description is quite complete: it covers every parameter, provides examples, and states preview behavior. An output schema exists, so not detailing the return payload is acceptable. It lacks a bit of clarity about how 'preview' relates to full data access, and it doesn't mention authentication requirements.

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 description coverage is 0%, but the description thoroughly compensates by explaining all seven parameters with formats, examples, default values, and enumerated options (e.g., frequency codes 1–8, formula codes 0–8, aggregation choices). This goes well beyond the bare input 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 opens with 'Fetch one or more EVDS series', a specific verb+resource combination, and 'with full API features and preview in chat' clarifies its role as a data-retrieval tool. This distinguishes it from sibling tools like evds_series_list or evds_categories, which handle metadata/listing rather than actual series values.

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

Usage Guidelines2/5

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

No explicit guidance is provided about when to use this tool versus alternatives; sibling tools such as evds_search_series or evds_get_datagroup_data are not mentioned. The parameter details imply usage for fetching and transforming series data, but there are no when-not-to-use conditions or alternative recommendations.

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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