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// Music & Audio

Music Release Metadata Reconciler

Reconcile track order, ISRCs, contributors, splits, territories, flags, and asset references before delivery.

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Format: Agent skill, not a browser app. You need an AI agent that can load its instructions and use the required tools.

Package requirements: SKILL.md-compatible agents that can run a local Python helper. Python 3.10 or newer on Windows, macOS, or Linux using only the standard library. One documented UTF-8 JSON evidence packet; no API key or provider account.

You get: result.json with PASS, REVIEW, BLOCK, or CANNOT_ASSESS report.md human-review handoff

Licence and purchase details

Review the package licence at the destination.

Review the offer and access method at your chosen marketplace. Agensi provides connected-agent access, not a download. Buying a skill does not include an AI-agent subscription or setup service.

Agensi access: This product’s bundled-script workflow through Agensi has not been verified here. Tests of other products do not establish this package’s compatibility. Local setup examples apply to separately obtained downloadable packages.

See tested hosts, versions and workflow limits.

What problem does Music Release Metadata Reconciler solve?

Release metadata is duplicated across distributor sheets, split records, assets, track order, territories, and explicit-content flags.

Use it to

What it returns

A representative input and result

fixture-backed sample
input Supply release.releaseId and trackOrder plus tracks with trackId, title, isrc, explicit, audioAssetRef, contributors with splitPercent, and territories.
result A deterministic PASS, REVIEW, BLOCK, or CANNOT_ASSESS result with stable finding codes, report, manifest, and SHA-256 receipts.

Access and approval boundaries

Known limitations

// choose with context

Is Music Release Metadata Reconciler the right skill?

Best fit

Release metadata is duplicated across distributor sheets, split records, assets, track order, territories, and explicit-content flags.

It returns

result.json with PASS, REVIEW, BLOCK, or CANNOT_ASSESS. report.md human-review handoff.

Do not use it as

It does not deliver music or query a distributor.

Compatibility, access, version, and licence

Reads or accesses
Declared local scope: one owner-selected local JSON input, one new owner-selected local output directory.
Compatibility
SKILL.md-compatible agents that can run a local Python helper. Python 3.10 or newer on Windows, macOS, or Linux using only the standard library. One documented UTF-8 JSON evidence packet; no API key or provider account.
Version
1.0.0
Licence
Review the package licence and seller terms at the linked destination.

What happens next

Open the Agensi listing, check the current offer and connect a supported agent. Agensi loads the skill through its connector; it no longer provides a download. Approve any purchase before use. Check Agensi’s current connection guide before changing an existing connection.

Questions

Does it connect to or change a live system?

No. It reads one local packet, writes one new local output directory, and makes no network request.

Does PASS prove the evidence or language is correct?

No. PASS only means no encoded rule fired in supplied normalized evidence.

What happens when evidence is missing?

The gate returns CANNOT_ASSESS or BLOCK; missing evidence never becomes a pass.

Is the result deterministic?

Yes. Findings are sorted and persisted outputs carry stable SHA-256 receipts.

Does the skill publish or make first-person claims?

No. It never publishes, contacts anyone, or adopts a founder, candidate, artist, or reviewer voice.

Music Release Metadata Reconciler keeps proof and approval boundaries visible.

The listing includes the tested package, realistic samples, declared permissions, and known limitations.

Get Music Release Metadata Reconciler on Agensi