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episode_guest_census

Identify recurring guests in a show's recent episodes by scanning description credits, revealing which guests return most often.

Instructions

Census recurring GUESTS across a show's recent episodes by mining description credits ("with X", "featuring X", "guest X") — who keeps coming back. Defaults to the 20 newest episodes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
show_idYesShow ID, spotify:show: URI, or open.spotify.com/show URL
max_resultsNoMax items to return (default: SPOTIFY_MCP_MAX_ITEMS env or 50)
episodes_limitNoNewest episodes to mine. Default 20
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise
Behavior3/5

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

With no annotations, the description carries the burden. It discloses the actual mining patterns ('with X', 'featuring X', 'guest X') which sets accuracy expectations, and the default scope of 20 episodes — though that default duplicates the schema's episodes_limit text. It does not confirm read-only behavior or state what happens when no recurring guests are found.

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 tight sentences, front-loaded with the verb+resource, and the default arrives in a scanable second sentence. No filler; every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-param tool with complete schema coverage, the call surface is well covered. The gap is return shape: with no output schema, the agent cannot tell whether it gets counts, rankings, or per-episode matches — 'who keeps coming back' only implies frequency output. An explicit return-format hint would make it complete.

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?

Schema description coverage is 100%, so the baseline of 3 applies. The description's only param-adjacent contribution is framing episodes_limit as the mining window, which the schema already documents ('Newest episodes to mine. Default 20'). It adds nothing on show_id formats or response_format distinctions beyond the schema.

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?

States a specific verb ('Census') + resource (recurring GUESTS across a show's recent episodes) and the mechanism (mining description credts with 'with X', 'featuring X', 'guest X'). The 'who keeps coming back' discriminator sets it apart from sibling census/report tools like featuring_density_report and artist_representation_census without opening their schemas.

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 'who keeps coming back' framing implies when to reach for this tool, and the defaut window sets scope. But it does not name alternatives or exclusion criteria, so among 300+ siblings an agent must infer routing purely from the purpose clause. That is implied guidance, not explicit.

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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