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StudioSphere Pulse — Audio Intelligence

estimate_cost

Read-onlyIdempotent

Get the exact price to analyze an audio file before committing. Always call this first. Returns cost in dollars and a job_estimate_id valid for 30 minutes. Free — never charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolsYesAnalysis tools to price. Available in v1.0: bpm, key, waveform. Coming soon: structure, chords.
audio_urlYesPublicly accessible URL of the audio file (MP3, WAV, FLAC, OGG, Opus).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
errorNoMachine-readable error code.
tokensNoEstimated Pulse tokens.
detailsNoAdditional structured context from Pulse.
messageNoHuman-readable recovery guidance.
cost_usdNoEstimated analysis cost in USD.
breakdownNoPer-tool token and cost estimate.
retryableNoWhether the caller may retry after changing state or waiting.
expires_atNoISO timestamp when the estimate expires.
content_typeNo
cost_displayNoHuman-readable USD estimate.
job_estimate_idNoEstimate identifier valid for the configured TTL.
normalize_sourceNo
duration_inferredNo
audio_url_originalNo
audio_url_normalizedNo
content_length_bytesNo
duration_estimate_secNoEstimated audio duration in seconds.

TDQS

A4.3/5.0
Behavior4/5

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

Beyond annotations (readOnlyHint=true, destructiveHint=false), the description adds that the tool is 'Free — never charged' and returns a job_estimate_id valid for 30 minutes. This discloses cost and validity aspects not covered by the annotations, enriching the agent's understanding without contradicting the structured hints.

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 concise sentences: purpose, usage order, and return details. It is front-loaded with the primary action, has no redundancy, and every sentence adds value.

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

Completeness5/5

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

For a simple two-parameter tool with an output schema, the description covers purpose, invocation order, return value (cost and ID), and cost implication. It does not need to explain return format because the output schema exists, making this contextually 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?

Both parameters (audio_url and tools) are fully described in the input schema, including enum values and URL formats. The description adds no additional parameter-specific details, so the baseline score of 3 is appropriate given the 100% schema coverage.

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 clearly states the tool's purpose: 'Get the exact price to analyze an audio file before committing.' It specifies the resource (audio file) and the verb (get exact price), and distinguishes from sibling tools like analyze_track by framing this as a pre-commit estimate.

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

Usage Guidelines4/5

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

The instruction 'Always call this first' provides clear when-to-use guidance relative to analysis. It doesn't explicitly name alternatives, but the directive strongly implies it should precede analyze_track. The context of 'before committing' further clarifies the intended use case.

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

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct role: cost estimation, analysis initiation, status polling, token balance, token pack listing/purchasing, payment linking, and trial creation. Even the two analysis-triggering tools (analyze_track and request_payment_link) are cleanly separated by account vs. non-account workflows.

Naming Consistency5/5

All eight tools follow a consistent snake_case verb_noun pattern (e.g., estimate_cost, list_token_packs, start_trial). The verbs are specific and predictable, and there are no mixed conventions or vague names.

Tool Count5/5

Eight tools strike a good balance for this domain: three cover the analysis pipeline (estimate, analyze, poll) and five cover billing/tokens/trial. Every tool serves a distinct purpose with no redundancy or bloat.

Completeness4/5

The set covers the full analysis workflow (cost estimation, submission, status polling) and token management (balance, packs, purchase, trial, payment link). A minor gap is the lack of job cancellation or historical job listing, but core user tasks are fully supported.