Opedd

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

With no annotations, the description carries the full burden. It discloses read-only nature via 'Browse' and 'Returns', notes the registry is public, and mentions filtering capabilities. However, it does not explain result ordering beyond 'recently issued', pagination details, or any rate limits, leaving some behavioral traits undisclosed.

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

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

The description is two sentences, front-loaded with the core purpose and followed by the two key filters. Every word contributes, with no redundancy or unrelated details.

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

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

For a simple read-only browsing tool with three optional parameters and no output schema, the description sufficiently covers what it returns and how to filter. It could mention the limit parameter or explicitly state read-only behavior, but these are already implied or covered by the schema, making it complete enough for the tool's complexity.

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

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

Schema coverage is 100% with descriptions for all three parameters. The description adds value by explaining the purpose of publisher_id ('explore all content from a specific publisher') and article_id ('see all licenses issued for a specific article') in natural language, going beyond the schema's bare definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as browsing the public Opedd license registry and specifies that it returns recently issued licenses and licensable content. It distinguishes itself from sibling tools by focusing on registry browsing and offering specific filters for publisher_id and article_id.

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

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

The description implies usage context (browse the registry, explore a publisher or article's licenses) but does not explicitly mention alternatives or when not to use this tool compared to siblings like lookup_content or list_feed. It provides useful context but lacks explicit exclusions or alternative guidance.

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

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

With no annotations, the description carries the full burden. It discloses auth requirements ('Public no-auth lookup'), latency expectations (milliseconds vs ~few seconds for custom domains), and the fact that it probes well-known platform endpoints in parallel. This is substantial behavioral context, though it does not cover failure modes or rate limits.

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

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

The description is front-loaded with the primary action and auth status, then provides return format and field semantics. It includes the unnecessary phase label 'Phase 12 Wave 3 W3.1' which adds noise, but otherwise every sentence contributes value.

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

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

Despite having no output schema, the description enumerates all return fields (platform, confidence, archive_method, forward_method, required_credentials, instructions) and explains how the key workflow fields are consumed. It also covers performance and auth, making it complete for a single-parameter tool.

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

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

The schema already documents the url parameter with 100% coverage, including the hostname-match short-circuit behavior. The description adds no additional parameter-specific semantics; it only reiterates behavior already in the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource: 'Detect the content platform behind a URL' and enumerates output platforms (Substack, Beehiiv, Ghost, Medium, Brevo, custom). It clearly distinguishes from sibling tools by focusing on platform identification and onboarding workflow rather than content retrieval or licensing.

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

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

The description states 'Public no-auth lookup' and 'Given a URL, identifies what platform powers it,' which implies the use case. It also explains that the returned archive_method and forward_method are read by Opedd's setup wizard, giving strong context for when to use it. However, it does not explicitly contrast with sibling tools or state when not to use it.

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

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

With no annotations provided, the description carries full burden. It discloses output fields and implies a read-only lookup, but it does not mention error handling, required permissions, or any edge cases (e.g., unavailable content). However, for a simple lookup tool, the disclosed behavior is adequate but not exhaustive.

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

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

Two sentences, front-loaded with the action and resource, then returns/usage instruction. Every sentence earns its place—no fluff, no repetition of schema details.

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

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

For a simple single-parameter tool with no output schema, the description covers the input (URL), the output (title, publisher, licenses, pricing), and the appropriate context ('Always call this first'). This is fully sufficient for an agent to select and invoke the tool correctly.

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

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

Schema coverage is 100% (url described as 'canonical URL'), so the baseline is 3. The description reiterates that lookup is 'by URL' but adds no extra semantic information beyond the schema, such as format expectations or non-canonical URL handling.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Look up' with a clear resource ('content on the Opedd registry by URL'), and further clarifies the lookup scope by listing returned data (title, publisher, license types, pricing). This clearly differentiates it from siblings like 'get_content' or 'browse_registry' by emphasizing licensing/cost information.

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

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

The phrase 'Always call this first to check if content is licensable and what it costs' gives explicit guidance on when to use the tool. It does not explicitly mention alternatives or when not to use it, but the directive is clear and contextually strong.

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

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

No annotations are provided, so the description must disclose behavioral traits. It reveals the HTTP method (GET), public no-auth access, pagination behavior, and the fact that sample articles contain RAG-extended metadata. It lacks rate limit or error details, but for a public read-only browse tool the disclosure is strong.

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

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

The description is compact and front-loaded with the primary purpose. Four sentences cover the function, return data, differentiation from a sibling, and use case. The bolded phrase highlights the tool's role without wasting words.

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

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

Given no output schema, the description compensates by naming the returned fields (article counts, pricing, plan, sample articles). It also covers auth, pagination, filters, and the intended usage context. This is complete for a public GET tool with five parameters.

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

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

Schema description coverage is 100%, so the baseline is 3. The description recaps filters (category, min_articles, verified status) but does not add information beyond the schema. The schema already provides details like case-insensitivity and default behavior for verified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (browse), the resource (Opedd publisher catalog), and what it returns (publishers with article counts, pricing, plan, sample articles). It explicitly distinguishes itself from the sibling tool browse_registry by noting the latter lists licenses, not publishers.

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

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

It names browse_registry as the alternative and explains the difference, and further contextualizes when to use it: 'useful pre-purchase scoping before buyers commit to enterprise-license POST.' This is explicit when/why guidance.

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

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

No annotations provided, but description covers the flow (Stripe client secret, emailed key), scope/tier behaviors, and mapping equivalents. Could add auth or rate limit notes.

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

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

Single paragraph with bullet-like lists for scopes and tiers; front-loaded purpose, but could use more structured formatting.

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

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

Given 9 params and nested object, description covers return value, key delivery, scope/tier options, and references Phase 10 docs for filter_rules. Lacks output schema but mentions return contents.

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

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

With 100% schema coverage, baseline is 3. Description adds value by explaining scope/tier enums and clarifying when publisher_ids is required vs ignored.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly specifies it purchases a bulk enterprise license covering multiple publishers, distinct from sibling purchase_license. Mentions return values and key mapping.

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

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

Implicitly distinguishes from purchase_license via 'bulk enterprise' wording and explains scopes and tiers to guide selection, but lacks explicit when-not-to-use guidance.

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

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

No annotations provided, so description carries full burden. It discloses return values (license key, certificate URL), side effect (Handshake Email), and license types. It does not mention payment charges or destructive nature, but overall transparent.

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

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

Two sentences plus a bullet-like list. Concise and front-loaded with the main purpose. The list of license types is dense but efficient. Slight improvement could be structuring the list better.

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

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

Given 8 params and no output schema, description covers key outputs, env vars, and license types. It could clarify article_id/article_url exclusivity and payment flow, but it's reasonably complete for a purchase tool.

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

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

Schema coverage is 100%, so baseline is 3. Description adds value by explaining env var fallbacks, license type meanings, and the license key format. This goes beyond schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool purchases a content license from the Opedd protocol using Stripe. It specifies the resource and action, and distinguishes from siblings like purchase_enterprise_license and verify_license.

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

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

The description explains when to use the tool (purchasing a standard license) and mentions environment variable fallbacks for convenience. It could explicitly mention when to use purchase_enterprise_license instead, but the context is clear.

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

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

No annotations are present, so the description carries the full burden. It discloses that the endpoint is public and no-auth, explains the two response shapes (raw JSON vs JSON-LD with HMAC-SHA256 signed receipt), and notes the publisher-side CDSM context. This is rich behavioral detail beyond basic read operation.

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

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

The description is informative and front-loaded with the core purpose, but includes some internal project references like 'Phase 12 Wave 1 W1.1' and 'Per INVARIANTS.md W1.6' that add noise. Overall, each sentence earns its place despite the verbosity.

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

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

Given the lack of output schema and annotations, the description provides comprehensive context: what the manifest contains, why an agent would use it, how the jsonld flag changes the response, and how this tool differs from the sibling attestation tool. It is complete for a simple GET endpoint.

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

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

The input schema covers both parameters with detailed descriptions (e.g., jsonld includes the signed receipt behavior). The tool description largely repeats this information without adding new parameter-level semantics. With 100% schema coverage, a baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Fetch a publisher's RSL Standard manifest via GET /rsl-manifest', which is a specific verb+resource. It also distinguishes this tool from the sibling 'article_53_attestation' by explicitly noting it is NOT the EU AI Act 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.

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

The description provides explicit guidance: it is a 'discovery surface for AI agents/crawlers wanting to know what's licensable from a publisher BEFORE going through the buyer-account signup flow' and explicitly contrasts it with the buyer-side `article_53_attestation` tool. This gives clear when-to-use and when-not-to-use guidance.

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

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

No annotations are provided, so the description carries the full burden. It states the tool 'verify[ies]' and 'returns license details,' implying a read-only, non-destructive operation, and it mentions 'blockchain proof status' as part of the response. While it doesn't explicitly state there are no side effects or prerequisites, the verification context is sufficiently transparent.

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

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

The description is two sentences long. The first sentence states the core purpose; the second lists return fields and gives a usage statement. Every sentence adds value, and the structure is front-loaded with the most important information.

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

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

Given the tool's simplicity (one parameter, no output schema, no annotations), the description is complete. It explains what the tool does, what it returns (listing specific fields), and when to use it. This is sufficient for an agent to invoke it correctly.

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

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

The input schema has 100% coverage for the single parameter, including its format ('OP-XXXX-XXXX'). The description does not add additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Verify the authenticity of an Opedd license key.' It uses specific verb+resource phrasing and lists various returned details (article title, publisher, license type, etc.), which distinguishes it from sibling tools like purchase_license or get_buyer_account.

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

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

The description provides explicit usage context: 'Use this to confirm a license is valid before using licensed content.' It does not mention alternatives or exclusions, but the intended scenario is clear enough for an agent to select this tool over others.

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