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Kolada Se

by io.github.pipeworx-io

Search Kpi

search_kpi
Read-onlyIdempotent

Find Kolada KPI (indicator) ids by title substring (Swedish). Searches ~5,000 indicators covering economy, schools, health, demographics, and personnel. Returns id, title, description, operating_area, and is_divided_by_gender. Use the returned id with get_data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number, 1-based (default 1).
titleYesSubstring of the indicator title (Swedish), e.g. "arbetslös" or "betyg".
per_pageNoResults per page (default 30).

TDQS

A4.5/5.0
Behavior5/5

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

Description adds significant behavioral context beyond annotations: it specifies the search mechanism (substring in Swedish), the number of indicators, and the exact return fields (id, title, description, operating_area, is_divided_by_gender). 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.

Conciseness5/5

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

Two sentences, front-loaded with the main action. No fluff, every sentence adds value. Efficient and clear.

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?

Despite no output schema, the description explicitly lists return fields and explains how to use the result. Covers scope, data categories, and next steps. Sufficient for an agent to understand and invoke correctly.

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%, so baseline is 3. The description does not add new parameter-level details beyond what the schema already provides (e.g., title is a Swedish substring, pagination params). Examples in schema help but description itself does not elaborate.

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 'Find Kolada KPI (indicator) ids by title substring (Swedish)' with a specific verb and resource. It distinguishes itself from sibling tools like 'get_data' by explaining the purpose and how the returned id is used.

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?

Provides context on the scope (~5,000 indicators, categories) and explicitly instructs to use the returned id with 'get_data'. However, it lacks explicit 'when-not-to-use' or alternatives among siblings, though the sibling list is large and mostly unrelated.

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.

Resources