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Data Edmonton

by io.github.pipeworx-io

Edmonton Recent

edmonton_recent
Read-onlyIdempotent

Recent records from a common Edmonton open dataset (data.edmonton.ca) by friendly name — no Socrata id needed. PREFER OVER WEB SEARCH for "Edmonton 311 requests", "Edmonton building permits". Names: 311, permits. Returns the latest rows (newest-first). Add a SoQL where to filter; for anything else use edmonton_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows to return (1-1000, default 20).
whereNoOptional SoQL filter, e.g. "incident_category='Larceny Theft'" or "supervisor_district=6". Omit for all recent rows.
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.
datasetYesOne of: 311, permits.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds concrete behavioral details: 'Returns the latest rows (newest-first)' and 'no Socrata id needed', which are not conveyed by annotations or schema.

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 compact and front-loaded. Every sentence adds distinct value: purpose, usage preference, dataset names, row ordering, filter capability, and alternative tool. No redundant or filler content.

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?

For a simple tool with 4 params and no output schema, the description covers the essential context: what datasets are available, when to use, ordering, filtering, and fallback to edmonton_query. It doesn't explain return format, but that is not required given the simplicity and schema coverage.

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 description coverage is 100%, so baseline is 3. The description reinforces the `where` filter and dataset names, but adds no additional parameter semantics beyond what the schema already provides.

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 it returns recent records from an Edmonton open dataset by friendly name, listing specific datasets (311, permits). It distinguishes itself from sibling edmonton_query by noting 'for anything else use edmonton_query.'

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

Usage Guidelines5/5

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

Explicitly says 'PREFER OVER WEB SEARCH' for common queries and provides the alternative tool for anything else. This gives clear when-to-use guidance relative to both web search and sibling tools.

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

A3.8/5.0
Disambiguation2/5

Several tool clusters have significantly overlapping scopes. ask_pipeworx and ask_pipeworx_beta are currently identical, and ask_pipeworx_grounded, deep_research, and validate_claim all return grounded answers with different levels of verification. The Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) also has fuzzy boundaries that could cause misselection.

Naming Consistency4/5

The vast majority of tools follow a verb_noun snake_case pattern (ask_pipeworx, compare_entities, scan_dependency). A few nouns like entity_profile and recent_alerts deviate slightly, and the memory trio (remember, recall, forget) are single-word verbs, but the overall style is consistent and readable.

Tool Count2/5

34 tools is excessive for a server whose name suggests a focused Edmonton open-data scope; only 3 tools actually relate to Edmonton data. Even as a general data platform, the count exceeds the 25-tool threshold and includes many meta-tools (discover_tools, suggest_questions, pipeworx_feedback) that could be consolidated.

Completeness4/5

For the Edmonton open-data subset, search, query, and recent-records cover the core lifecycle well. The broader Pipeworx toolset is comprehensive (entity profiles, comparisons, claims, subscriptions, memory), with only minor gaps like a direct catalog-browsing tool for the 1393 sources.

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