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snapshot_integrity_check

Validate Spotify data snapshots by checking JSON parsing, required _meta keys, and that track_count matches the tracks array. Run on a single snapshot or all to ensure integrity.

Instructions

Validate one snapshot (or all of them): JSON parses, required _meta keys exist, and the declared track_count matches the tracks array

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
snapshotNoOne snapshot (id/filename/path); omit to check ALL snapshots
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 behavioral burden. It discloses the validation criteria (JSON parse, #_meta keys, track_count match), which is genuinely useful, but it never says what happens on failure, whether the operation is read-only, or what the response shape is. For a validation tool, failure semantics are a notable omission.

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?

A single front-loaded sentence that opens with the verb, states scope, then colon-delimits the three integrity checks. There is zero waste and every phrase 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 2-optional-param tool with no output schema and no annotations, the description adequately covers what the tool checks, and the schema covers parameters. But it lacks failure behavior, return-format semantics beyond the enum labels, and guidance about when validation is needed (e.g., before restore). An agent could invoke it correctly yet be unsure how to interpret the result.

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%: snapshot explains id/filename/path and omit-to-check-all, and response_format documents each enum value. The description adds no param-level meaning beyond what the schema already provides, so the baseline 3 applies.

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 has a specific verb ('Validate') and resource ('snapshot(s)'), and it enumerates the exact checks performed: JSON parses, required _meta keys exist, and track_count matches the tracks array. This is clear on its own, but it does not differentiate itself from near-siblings like snapshot_integrity_report or snapshot_stats_report, which could plausibly overlap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says when it applies ('one snapshot (or all of them)') and the schema adds scope semantics for the snapshot parameter, but there is no guidance on when to choose this tool over alternatives such as snapshot_integrity_report or read_playlist_snapshot. Given the large set of snapshot siblings, the absence of when/when-not guidance is a real gap.

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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