Framekeep Public Discovery

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

With no annotations, the description carries the burden of disclosing behavior. It mentions 'public' suggesting no auth, but it doesn't explicitly state read-only nature, return format, or side effects. The phrase 'privacy boundaries' adds some context, but a bit more detail on what exactly is returned would improve transparency.

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?

A single, front-loaded sentence immediately conveys the tool's purpose. No unnecessary words, perfectly concise.

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 there are no parameters, no output schema, and the tool is a simple overview retrieval, the description sufficiently covers what the agent needs to know: what the tool returns and its scope (public, privacy boundaries). No significant gaps.

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?

There are zero parameters, so the baseline is 4. The description doesn't need to explain any parameter semantics, and the schema is empty, making the tool trivially parameterized.

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 ('Return') and clearly identifies the resource ('concise public overview of Framekeep and its privacy boundaries'). It distinguishes itself from siblings by focusing on overview and privacy, not start options or list of resources.

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 use when an overview is needed, but it doesn't explicitly contrast with siblings or give when-not-to-use guidance. The context is clear, so no further exclusions are necessary for a simple read-only tool.

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 transparency burden. It adds context like 'privacy-safe' and 'free no-account,' but does not disclose potential side effects, return format, or any operational details beyond the act of returning links.

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 a single, focused sentence that starts with the verb and clearly states the output. It contains no filler and is easy to parse at a glance.

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 (0 params, no output schema), the description is adequate for understanding its purpose. It could define 'gallery' or 'studio' more explicitly, but the core function is clear enough for selection.

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 tool has zero parameters, and the schema is empty with 100% coverage by default. The description adds no parameter-specific details, but none are required; baseline for 0 params is 4.

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 the specific verb 'Return' and names the resource: 'privacy-safe links for creating a free no-account gallery or a reusable studio.' This clearly distinguishes it from sibling tools like get_framekeep_overview and list_framekeep_public_resources.

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 offers no explicit guidance on when to use this tool versus its siblings. It does not mention alternatives, prerequisites, or typical scenarios, leaving usage entirely implicit.

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?

The description only says 'List' and does not disclose whether the operation is read-only, requires authentication, or how results are returned. With no annotations provided, the description carries full responsibility for behavioral transparency, and this minimal information is insufficient.

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 a single, clear sentence with the verb 'List' front-loaded. There is no redundant wording or filler, making it highly concise and well-structured.

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?

With no output schema and no annotations, the description is minimal. It does not specify the return format (e.g., an array of URL strings) or any caveats about the URLs. This lack of context could leave the agent uncertain about what to expect from the 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 tool accepts zero parameters, so the input schema fully covers this dimension. The description adds no parameter details, but none are needed, making the baseline of 4 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 identifies the tool's purpose using the verb 'List' and a specific resource: Framekeep's preferred public documentation and discovery URLs. This is distinct from sibling tools like get_framekeep_overview and get_framekeep_start_options, which focus on different aspects.

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?

No guidance is provided on when to use this tool versus its siblings. The description only states what the tool does without indicating situations where it is the best choice or when to prefer alternatives.

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