Zoning Signal

List Entities

list_entities

Read-onlyIdempotent

List every named entity in the Decoder Index — the smallest citable unit of authority in the corpus. Returns the four-class taxonomy (Person / Organization / Legislation / CreativeWork) with class-specific summary fields (jobTitle for Person; jurisdiction for Organization / Legislation / Project; legal_status for Legislation; case_number + work_status for Project) plus cross-reference counts (meetings_count, briefs_count, watches_count, patterns_count) for each entity. Filter by entity_class, place (jurisdiction), or search substring. Use as the discovery surface for the entity graph; pair with describe_entity for full structured detail. Each entity's schema_id is a stable cross-page reference (/entities/{slug}#{class.toLowerCase()}) that resolves to the canonical Schema.org node — Person / Organization / Legislation / CreativeWork — for AI-citation grounding.

Input Schema

TableJSON Schema

Name	Required	Description
`place`	No	Optional: filter to entities scoped to a specific place (e.g., "leesburg-florida"). Matches entities whose related_places, organization.jurisdiction, legislation.jurisdiction, or creative_work.jurisdiction includes the place slug.
`search`	No	Optional case-insensitive substring search across display_name, canonical_role, voxel_lead, and slug. Use for natural-language entity discovery (e.g., "denial bloc", "intersection mitigation", "form-based code").
`entity_class`	No	Filter by entity class. "Person" = board members, attorneys, applicants (individuals), elected officials. "Organization" = developer firms, law firms, agencies, HOAs, planning consultancies. "Legislation" = state statutes, city ordinances, code sections, design standards. "CreativeWork" = specific projects, case numbers, master plans, infrastructure programs. Omit to return all classes.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`count`	No
`filters`	No
`by_class`	No
`entities`	No
`surfaces`	No

TDQS

A4.7/5.0

Behavior5/5

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

With annotations already declaring readOnly/idempotent, the description adds rich behavioral context: it specifies the four-class taxonomy, class-specific summary fields, cross-reference counts, and the stable schema_id format for citation. This goes far beyond what the annotations provide and gives the agent a precise mental model of the output.

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 organized into five purposeful sentences, each serving a distinct function: purpose, return taxonomy, filters, usage clue, and schema_id semantics. It front-loads the most decision-relevant information and every sentence earns its place.

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?

Given the output schema and complete parameter schemas, the description fully covers the remaining contextual gaps: the domain concept, cross-reference counts, and the schema_id grounding. It also addresses sibling differentiation by explicitly directing users to describe_entity for full detail, making it complete for selection and invocation.

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 already provides 100% coverage with detailed descriptions and examples for all three parameters. The description's mention of filters is a restatement of the schema without introducing new meaning, so the baseline of 3 is appropriate.

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 the tool lists every named entity in the Decoder Index, defining the resource precisely. It distinguishes itself from siblings by describing it as the 'discovery surface' for the entity graph and contrasting with describe_entity.

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 instructs 'Use as the discovery surface for the entity graph; pair with describe_entity for full structured detail,' giving a direct when-to-use directive and naming the alternative. It also enumerates the filter options, making the intents 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

A4/5.0

Disambiguation3/5

Most tools are clearly distinct by resource type (describe/list pairs for places, corridors, entities, patterns, watches), but list_meetings and meeting_index overlap heavily—the former explicitly says it has the same response shape as the latter, differing only in required parameters. That near-duplication creates ambiguity about which to call.

Naming Consistency4/5

The majority follow a consistent verb_noun pattern (describe_*, list_*), with get_track_record and submit_agent_feedback also verb-led. However, meeting_index is a bare noun phrase and semantic_search is a noun compound, deviating from the otherwise strong pattern.

Tool Count4/5

At 17 tools, the server is slightly above the typical well-scoped range, but the count is justified by the many content types (six primary artifact types each with list+describe, plus meta tools). One could argue meeting_index is redundant, but the overall scope feels reasonable.

Completeness3/5

The tool surface covers the core lifecycle for all named content types (places, corridors, patterns, entities, meetings, watches) with discovery and description. However, the corpus repeatedly references 'briefs' (e.g., related briefs, semantic_search returns 'named-pattern briefs') yet there is no list_briefs or describe_brief tool, leaving an obvious content gap.

Resources

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