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search_history_stats

Analyze Spotify search history to surface top queries, content-type breakdown, and recency patterns. Get local-only insights into listening behavior without consuming API quota.

Instructions

Analytics over the local search-history sidecar: top queries, type breakdown, recency. Quota: 🟢 local only (no API).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoTop N queries to show (default 10)
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 provided, the description carries the full disclosure burden, and it does add real behavioral context: 'local only (no API)' discloses the quota/backing-store trait and heavily implies a read-only, side-effect-free analytics operation. It does not explicitly state read-only behavior or describe what 'type breakdown' or 'recency' produce, but for a simple local stats tool the disclosed locality/cost signal is meaningful.

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 short sentences with zero filler: the first front-loads what the tool does and its output facets, the second conveys the quota trait in a compact emoji-prefixed tag. 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?

Given the tool's low complexity (two optional params, no required fields, no output schema) and the presence of a response_format parameter that governs output shape, the description is nearly complete: it covers the domain (search-history analytics), the data source (local sidecar), and the cost profile (no API). The only minor gap is not previewing the shape of the 'concise'/'detailed' output, but the schema's response_format descriptions already carry that weight.

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 both parameters (top_n, response_format) are already documented with defaults, ranges, enum values, and format meanings—meeting the baseline of 3. The description's mention of 'top queries' loosely maps to top_n but adds no new parameter-level detail 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 a specific operation ('Analytics over the local search-history sidecar') and enumerates concrete outputs (top queries, type breakdown, recency), so an agent knows what this tool does. It implies differentiation from siblings like search_history and history_search through the word 'Analytics', but does not explicitly name a sibling or draw the contrast, so it stops short of a 5.

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 quota note ('🟢 local only (no API)') provides useful cost/locality context that helps an agent decide when calling is cheap, and the analytics framing implies use for summary/statistics tasks over search history. However, there is no explicit when-to-use vs. alternatives guidance—e.g., it never says 'for raw history lookups use search_history'—so routing depends on 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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