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Kolada Se

by io.github.pipeworx-io

Get Data

get_data
Read-onlyIdempotent

Fetch numeric KPI values from Kolada for a specific indicator (kpiId), Swedish municipality or region (municipalityId), and year. Returns value rows broken down by gender: T=total, K=women (kvinnor), M=men (män); non-gendered KPIs return only T.municipalityId from list_municipalities. Returns values per gender ("T" total, "K" women, "M" men); non-gendered KPIs report only "T".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesFour-digit year, e.g. 2022.
kpiIdYesKPI id from search_kpi, e.g. "N15428".
municipalityIdYesMunicipality/region id from list_municipalities, e.g. "0180" (Stockholm).

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already indicate readOnly and idempotent behavior. The description adds useful context about the return format (gender breakdown, non-gendered KPIs) and no contradictions. It adds beyond 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?

The description is two sentences but contains redundancy (gender breakdown repeated). It is front-loaded with the main purpose, but could be more concise.

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?

No output schema exists, so the description partly explains the return structure (gender breakdown). However, it lacks details on error cases, response format, or potential issues. The fragment 'T.municipalityId from list_municipalities' is confusing.

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 100% with descriptions for all parameters. The description repeats the role of parameters (e.g., 'municipalityId from list_municipalities') but adds no new syntactic or semantic details beyond what's in the schema.

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?

The description clearly states it fetches numeric KPI values for a specific indicator, municipality, and year. It uses a specific verb and resource, but does not explicitly differentiate from siblings like compare_entities or search_kpi.

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?

The description implies that the tool is used when you have a specific kpiId, municipalityId, and year, and hints at using sibling tools (list_municipalities, search_kpi) to get IDs. However, it lacks explicit guidance on when not to use it or 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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TDQS

A3.7/5.0
Disambiguation2/5

Multiple tools overlap heavily: ask_pipeworx, ask_pipeworx_beta (explicitly identical when no routing candidate is active), ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions through the same underlying router. The prediction-market cluster (polymarket_edges, polymarket_arbitrage, bet_research, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) has substantial purpose overlap that requires reading long descriptions to disambiguate.

Naming Consistency3/5

Mostly snake_case, and the pipeworx_/polymarket_/ask_ prefixes give some structure, but conventions are mixed: some tools are verb_noun (list_municipalities, get_data), some are bare verbs (forget, recall, remember), and some are noun phrases (entity_profile, deep_research, bet_research, recent_changes). The inconsistent prefixing across meta-tools (ask_, deep_, entity_, scan_, validate_) makes the surface feel less predictable than it could be.

Tool Count2/5

35 tools is on the heavy side, but the bigger problem is that the server name 'Kolada Se' matches only 4 tools (search_kpi, list_municipalities, list_org_units, get_data), while the other 31 tools belong to unrelated domains (Pipeworx data routing, prediction markets, memory, subscriptions, AI visibility). This is a severe scope mismatch that makes the count feel bloated and unfocused.

Completeness3/5

For the Kolada domain named by the server, the surface is minimal: you can search KPIs, list municipalities, list org units, and fetch single-KPI data, but there is no multi-year bulk fetch, cross-municipality comparison, or unit-level data retrieval. The broader Pipeworx/prediction-market surface is fairly feature-complete, but it is not what the server name implies, so the set as a whole leaves the apparent domain thinly covered.

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