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Neso

by io.github.pipeworx-io

Neso Query Data

neso_query_data
Read-onlyIdempotent

Query rows from a NESO GB energy dataset resource (CKAN DataStore) by resource_id — UK electricity demand, wind generation forecasts, carbon intensity, balancing data. Supports exact-match filters (field->value object), full-text query, limit, offset. Returns field names/types plus records. Example: neso_query_data({ resource_id: "aec5601a-7f3e-4c4c-bf56-d8e4184d3c5b", limit: 20 })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoOptional sort, e.g. "TARGETDATE desc".
limitNoMax rows, 1-200 (default 20).
queryNoOptional full-text search over the rows.
offsetNoPagination offset (default 0).
filtersNoOptional exact-match filters, e.g. { "DAYSAHEAD": 1 }.
resource_idYesResource id from neso_dataset_resources (must have datastore_active true).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "limit": 20,
+    "resource_id": "aec5601a-7f3e-4c4c-bf56-d8e4184d3c5b"
+  },
+  {
+    "filters": {
+      "DAYSAHEAD": 1
+    },
+    "limit": 50,
+    "resource_id": "aec5601a-7f3e-4c4c-bf56-d8e4184d3c5b",
+    "sort": "TARGETDATE desc"
+  }
+]
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds that the tool returns field names/types plus records, which is useful but does not disclose behavioral traits beyond what annotations provide. No contradictions.

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 three sentences, front-loaded with the primary action, lists key features concisely, and includes a relevant example. No extraneous content; every sentence adds value.

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 6 parameters with nested objects and no output schema, the description explains the return format (fields + records) and provides an example. It does not cover error handling or pagination details beyond offset/limit, but overall is sufficient for an agent to use the tool effectively.

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?

The input schema has 100% description coverage for all parameters. The description adds a brief summary ('exact-match filters', 'full-text query') and an example, but does not significantly enhance understanding beyond the schema provided. Baseline 3 applies.

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 queries rows from a NESO GB energy dataset resource by resource_id, and lists examples like electricity demand and wind forecasts. However, it does not explicitly distinguish from sibling tools like neso_dataset_resources or neso_demand_forecast, so the purpose is clear but not fully differentiated.

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 usage context by mentioning resource_id from neso_dataset_resources, but does not provide explicit guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. The example shows typical usage but no when-not-to-use criteria.

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

A3.9/5.0
Disambiguation2/5

The ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded trio is genuinely confusing — beta is explicitly identical to stable, and grounded differs only in output format, so agents will struggle to pick the right one. The six Polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread, bet_research) also blur together despite distinct purposes, and ai_visibility_check vs scan_competitor_ai_presence overlap heavily.

Naming Consistency4/5

Naming is largely consistent: snake_case throughout, with a strong verb-first pattern (list_subscriptions, resolve_entity, validate_claim, compare_entities, discover_tools) and clear domain prefixes for clusters (neso_, pipeworx_, polymarket_). The only inconsistency is the ask_pipeworx family, which differentiates by bare suffix (_beta, _grounded) rather than a descriptive verb.

Tool Count3/5

35 tools is on the heavy side, but the server is a broad multi-domain data platform (SEC, FDA, FRED, NESO, Polymarket, npm, memory, subscriptions, discovery) where the count is arguably justified. Several tools could be consolidated — the three ask_pipeworx variants are redundant, and scan_competitor_ai_presence largely wraps ai_visibility_check — which would tighten the surface meaningfully.

Completeness4/5

Coverage is strong across the stated domains: lookups, deep research, entity resolution, claim verification, comparisons, memory lifecycle (remember/recall/forget), subscription lifecycle (subscribe/unsubscribe/list/recent_alerts), discovery (discover_tools, suggest_questions), feedback, and trending. Minor gaps exist (no direct document-fetch tool, scan_dependency is npm-only in v1) but nothing that creates a dead end.

Resources