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Glama

Describe Corridor

describe_corridor
Read-onlyIdempotent

Return the dossier projection for a corridor, in the requested cognitive lens. Same lens enum and default as describe_place. Corridor projections surface cross-municipal dialectics and shared-infrastructure dynamics that no single place dossier captures.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lensNoThe cognitive position to project. Defaults to "synthesis". Canonical lenses: developer, investor, broker, attorney, business, resident, civic-leader. Aliases route to canonical: legal/lawyer/counsel/regulator → attorney; realtor/intermediary → broker; civic/government → civic-leader; homeowner → resident; operator/site-selector → business; builder → developer.synthesis
slugYesThe corridor slug (e.g., "us-27-south-lake"). Use list_corridors to discover available slugs.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
lensYes
slugYes
typeYes
titleNo
claimsYes
freshnessYes
projectionYes
frontmatterNo
record_statusNo
available_lensesNo
lens_was_requestedNo
fell_back_to_synthesisNo

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare the tool as readOnly, idempotent, and non-destructive. The description adds useful behavioral context about the nature of the output (a 'dossier projection' with a cognitive lens) and the kinds of insights it surfaces (cross-municipal dialectics, shared-infrastructure dynamics). 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 with no filler. The first sentence states the core function, the second clarifies the lens system and differentiates from describe_place. Perfectly front-loaded and appropriately sized.

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?

For a read-only lookup tool with an output schema, the description fully covers purpose, the cognitive lens concept, the unique value vs. alternatives, and references the right sibling for slug discovery (list_corridors in the schema). Nothing essential is missing given the tool's simplicity.

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 provides 100% coverage: both slug and lens have detailed descriptions, including an enum list and alias routing. The tool description adds only a cross-reference to describe_place's lens enum, which is redundant given the schema already lists the exact enum values. With high schema coverage, the description doesn't need to compensate.

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's action and resource: 'Return the dossier projection for a corridor, in the requested cognitive lens.' It distinguishes itself from sibling describe_place by noting that corridors surface 'cross-municipal dialectics and shared-infrastructure dynamics that no single place dossier captures.' This makes the tool's unique scope immediately clear.

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 implies when to use this tool via the alternative reference 'Same lens enum and default as describe_place' and the contrast with single-place dossiers. It doesn't explicitly say 'use describe_place for single places' or list exclusions, but the context effectively guides the agent to choose this tool for corridor-level cross-municipal analysis.

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.

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