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Glama

fetch_series

Retrieves selected time series from a source, applies frequency, aggregation, and formula transforms, then writes results to the local silver layer and returns a summary plus recent rows.

Instructions

Serileri çeker ve yerel silver katmanına yazar. Tarihler YYYY-AA-GG. freq: D,B,W,SM,M,Q,S,A; agg: avg,min,max,first,last,sum; formula: 0 düzey, 1 %değişim, 3 yıllık %değişim. Özet ve son max_rows satırı döner.

Input Schema

NameRequiredDescriptionDefault
aggNo
endNo
freqNo
startNo2010-01-01
seriesYes
sourceNoevds3
formulaNo
max_rowsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations exist, so the description carries the burden. It does disclose two important traits a schema cannot: the tool writes to a local silver layer (a mutation/persistence side effect) and returns a summary plus the last max_rows rows. It omits overwrite/refresh behavior, auth, rate limits, and error handling for bad codes.

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?

Front-loaded with the action and side effect, then dense enum listings with no filler. The telegraphic style is efficient, though a few cells (formula meanings, source) are compressed to the point of ambiguity.

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

Completeness3/5

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

For an 8-parameter tool with no output schema and no annotations, the return format and enum domains are covered, which is the critical part. Still missing are what 'source' values are valid, what happens to previously written silver data on re-fetch, and behavior on invalid series codes.

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?

With 0% schema coverage this is the description's main job, and it delivers the enum domains for freq (D,B,W,SM,M,Q,S,A), agg (avg,min,max,first,last,sum), formula (0/1/3) and the date format YYYY-AA-GG. It leaves 'series' format, 'source' alternatives, and 'max_rows' only implicitly defined ('last max_rows rows').

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Serileri çeker') and adds a concrete side effect ('yerel silver katmanına yazar'), which is more than a name restatement. It doesn't name the sibling it complements, but the fetch-vs-discover split against discover_series is inferable.

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

Usage Guidelines3/5

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

Usage is only implied: an agent can guess this is the step after discover_series, but the description never states when to call it, prerequisites, or what to do when a series code is unknown. No alternatives or exclusions are given.

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