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Read a publisher's RSL licence terms

rsl_get
Read-onlyIdempotent

Fetch a publisher's RSL Standard manifest so AI agents can discover licensable content and CDSM Article 4(3) opt-out status before buyer signup.

Instructions

Fetch a publisher's RSL Standard manifest via GET /rsl-manifest (Phase 12 Wave 1 W1.1). Public no-auth endpoint — discovery surface for AI agents/crawlers wanting to know what's licensable from a publisher BEFORE going through the buyer-account signup flow. Returns the 4 canonical license types (ai_retrieval, ai_training, human_per_article, human_full_archive) the publisher has opted into, plus the EU CDSM Article 4(3) opt-out posture (tdm_reservation). Set jsonld: true to request the JSON-LD shape with embedded HMAC-SHA256 signed receipt over the CDSM Article 4(3) reservation state + tdm:reservationSignedAt timestamp — regulators can post-hoc verify the reservation was the claimed value at the claimed time. Default jsonld: false returns the raw RSL Standard JSON manifest. Per INVARIANTS.md W1.6: this is the PUBLISHER-side CDSM Article 4(3) declaration surface. It is NOT an EU AI Act Article 53 attestation (which is buyer-side, JWT-auth, via article_53_attestation tool).

Input Schema

NameRequiredDescriptionDefault
jsonldNoIf true, request JSON-LD shape (Accept: application/ld+json) with embedded HMAC-SHA256 signed receipt. Default false returns raw RSL Standard JSON shape.
publisher_idYesUUID of the publisher whose RSL manifest to fetch. Publisher must be verified.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.7

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them: it discloses the endpoint is public no-auth, that requesting jsonld:true embeds an HMAC-SHA256 signed receipt with a tdm:reservationSignedAt timestamp, and what the default response shape is. That is exactly the behavioral context annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core purpose and the no-auth/discovery framing, and most sentences earn their place. It is dense with internal references ('Phase 12 Wave 1 W1.1', 'INVARIANTS.md W1.6') that add no value to an invoking agent.

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?

With no output schema, the description carries the return-value burden and does so: it enumerates the four license types and the tdm_reservation field, and distinguishes the JSON vs JSON-LD shapes. Nothing needed to call the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: it explains why jsonld:true exists (regulators can post-hoc verify the reservation value and time) and confirms the default is the raw RSL Standard JSON shape. It does not add format detail for publisher_id beyond the schema's UUID/verified note.

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?

States a specific verb and resource ('Fetch a publisher's RSL Standard manifest via GET /rsl-manifest') and pins the exact shape returned (4 canonical license types plus the CDSM Article 4(3) opt-out posture). It also explicitly distinguishes itself from the confusable sibling article_53_attestation.

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

Usage Guidelines5/5

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

Gives an explicit when-to-use ('discovery surface ... BEFORE going through the buyer-account signup flow') and an explicit when-not ('It is NOT an EU AI Act Article 53 attestation ... via article_53_attestation tool'). The alternative and the condition that selects it are both named.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.