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show_backlog_report

Identify podcast subscriptions with large unplayed backlogs by showing hours of unplayed episodes and newest-episode age per show, helping you decide which podcasts to unsubscribe from.

Instructions

Per saved podcast show: unplayed episodes (resume_point), hours of backlog and newest-episode age — decide what to unsubscribe from. Quota: 1 + N reads (budgeted).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNobacklog_hours
max_showsNoBudget for per-show episode paging. Default 25.
min_hoursNoOnly surface shows with at least this many backlog hours. Default 0 (all).
max_resultsNoMax items to return (default: SPOTIFY_MCP_MAX_ITEMS env or 50)
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise
Behavior4/5

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

With no annotations present, the description carries the burden, and it does useful work: 'Quota: 1 + N reads (budgeted)' discloses a concrete cost profile, and 'reads' signals a non-mutating operation. It does not go into authentication, failure modes, or pagination details, but this is strong extra context beyond the schema.

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 two tight sentences: the first front-loads scope, output fields, and purpose, while the second adds the quota warning. There is no filler, repetition of schema fields, or unnecessary detail.

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?

There is no output schema, but the description names the key returned fields and the cost behavior; combined with the well-documented input schema, an agent has enough to call the tool with defaults. It would be slightly more complete if it explicitly distinguished itself from show_backlog_plan and stale_saved_shows_plan, but it is not missing critical invocation information.

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 80%, and the parameters already carry meaningful descriptions for max_shows, min_hours, max_results, and response_format, so the baseline is 3. The description adds only loose context about what 'backlog_hours' and 'newest' refer to and does not materially clarify parameter formats beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the concrete data a caller gets per saved show — unplayed episodes with resume_point, backlog hours, and newest-episode age — and gives an explicit decision purpose: deciding what to unsubscribe from. It is clear enough to identify the tool's role, though it leans on the tool name for the 'report' verb and does not explicitly contrast it with similar show-planning siblings.

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?

It communicates a clear use case ('decide what to unsubscribe from') and signals that the call is quota-budgeted. However, it does not name alternatives such as show_backlog_plan, stale_saved_shows_plan, or shows_without_new_episodes, nor does it state when not to use this tool, so the agent must infer selection from the field list.

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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