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Arcgis Lakecountyil

by io.github.pipeworx-io

Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

TDQS

A3.8/5.0
Behavior1/5

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

The description states 'Set mark_read:true to flag returned events read so the next call only shows newer ones,' which implies state mutation. However, annotations declare readOnlyHint=true, directly contradicting that side effect. This is an annotation contradiction, so score is 1.

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 five sentences, front-loaded with purpose, and each sentence adds value: return payload, filtering, mark_read behavior, and polling/HTTP alternative. No filler.

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 read-tool with 5 optional parameters and no output schema, the description covers purpose, return fields, filtering, mark_read, and an alternate access method. The return payload is partially described, and parameter details are in the schema. It is reasonably complete, though the contradiction with readOnlyHint is a gap.

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?

Schema covers all 5 parameters (coverage 100%), so baseline is 3. The description adds beyond schema by explaining mark_read semantics (flags events read so next call only shows newer ones) and giving an example type 'sec_8k'. This extra guidance justifies a 4.

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 opens with 'Pull fired events from your subscription feed'—a specific verb+resource. It further clarifies the tool returns alerts with source, citation_uri, and raw payload, differentiating it from siblings like list_subscriptions or recent_changes.

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?

The description explains polling is fine and mentions the same feed is available at a direct HTTP endpoint for scripts/dashboards, giving an alternative. It does not explicitly state when-not-to-use, but the context is clear.

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 have overlapping purposes: ask_pipeworx and ask_pipeworx_beta are explicitly identical, while ask_pipeworx_grounded, deep_research, validate_claim, and entity_profile all perform data lookups with only subtle differences. discover_tools and suggest_questions also serve similar onboarding/exploration roles.

Naming Consistency4/5

Tool names are uniformly snake_case and generally follow a verb_noun or noun_phrase pattern (e.g., ask_pipeworx, query_layer, entity_profile, remember). There is a slight mix between verb-first and noun-first names but no chaotic conventions like camelCase or inconsistent verb tense.

Tool Count2/5

At 34 tools, the count is well above the typical 15-25 range for a coherent server. More critically, the server is named 'Arcgis Lakecountyil' but only 3 tools (search_datasets, layer_info, query_layer) actually relate to ArcGIS; the remaining 31 tools are a broad Pipeworx data platform, creating a severe scope mismatch that makes the count feel excessive and unfocused.

Completeness2/5

For the ArcGIS domain implied by the server name, the surface is barely complete: it offers search, schema inspection, and querying, but no create, update, delete, or management capabilities. Conversely, the Pipeworx side is relatively rich, but that doesn't match the server's stated purpose, leaving the overall set incomplete for its apparent intended use.

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