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FlightFinder Aviation Safety Data

get_narrative

Read-onlyIdempotent

Fetch an investigation narrative by (source, case id). Open-licensed sources return full text; others return a ≤300-char excerpt plus a source_url deep link (per-source licensing policy). id URL-encoding is handled for you — pass the raw case id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesthe source’s own case id
sourceYessource code, e.g. "ntsb" (see list_sources)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral detail beyond that: open-licensed sources return full text while others return a limited excerpt plus a source_url deep link, and id URL-encoding is handled automatically. This gives the agent important expectations about varying outputs.

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 tight sentences with no filler. The core action is front-loaded, followed by the two most useful operational caveats: licensing-dependent output and automatic URL-encoding. Every sentence earns its place.

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?

The description is sufficient for a read-only, two-parameter tool with a full input schema and an output schema. It covers the important licensing behavior and encoding detail. Minor gaps such as explicit error or not-found behavior are not necessary given the output schema and simple invocation model.

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 coverage is 100%, so the baseline is 3. The description adds valuable parameter guidance by explicitly stating that 'id URL-encoding is handled for you — pass the raw case id,' which prevents a common mistake. It also reinforces that source is a source code, though the schema already covers that.

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 a specific verb and resource: 'Fetch an investigation narrative by (source, case id).' It clearly distinguishes this tool from siblings like search_accidents or get_accident by identifying the required lookup key and mentioning the licensing-dependent return behavior.

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 the tool should be used when you already know a source and case id, and the schema points to list_sources for valid source codes. However, it does not explicitly contrast with alternatives such as search_accidents or explain when not to use it, leaving the routing largely to inference.

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

A4.1/5.0
Disambiguation5/5

Each tool maps to a distinct resource or dataset: accidents, narratives, sources, airport references, and the three FAA summary datasets. Even the get/search accident pair is clearly split by retrieve-by-ID versus filtered-search, so an agent should not struggle to pick the right tool.

Naming Consistency4/5

All names use snake_case and are readable, with noun-style dataset tools like wildlife_strikes and laser_incidents alongside verb-prefixed actions like search_accidents and list_sources. This is a minor deviation from a strict verb_noun convention, but it remains predictable.

Tool Count5/5

Nine tools is appropriate for a safety-data server that spans an accident corpus, narratives, source metadata, airport lookups, and multiple FAA datasets. Each tool earns its place and there is no obvious bloat or thinness.

Completeness4/5

The surface covers accident search/retrieval, narrative access, source metadata, airport resolution, and three FAA summary datasets. Notable gaps are the lack of occurrence-level retrieval for drone/laser/wildlife events and no explicit slug/autocomplete endpoint for aircraft families, but agents can usually work around these.

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