Thisispaper

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

Annotations already indicate read-only; description adds context by listing the returned fields, which aids in understanding the tool's behavior beyond the schema and annotations.

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-loads the main purpose, and includes only essential information with no wasted 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?

For a simple tool with one parameter and no output schema, the description covers the necessary context: what it does, what it returns. Minor omission: not mentioning if the id is case-sensitive or any other constraints, but not critical.

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% and already describes the parameter as a project id from search. The description repeats this without adding new meaning, so it meets the baseline for high coverage.

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 it retrieves a full record for a Thisispaper project by id, specifying returned fields (title, text, public url). However, it does not differentiate from sibling 'get_project' which may have a similar function.

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 after search by referencing 'id returned by search', but lacks explicit when-to-use or when-not-to-use instructions compared to alternatives like 'get_project' or 'similar_projects'.

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?

Annotations provide basic hints, but the description adds key behavioral traits: the key is shown only once, there is a limit of 3 keys per email, and the key format for authorization. This provides valuable context beyond annotations.

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 three sentences with no wasted words. It front-loads the purpose and efficiently covers usage, limits, and key format.

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 single-parameter tool with no output schema, the description covers all necessary context: purpose, constraints, usage instructions, and limits. No gaps remain.

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 with a description for the email parameter. The tool description reinforces the parameter's meaning ('for an email address') and adds constraints ('Max 3 keys per email'), but does not significantly extend beyond the schema.

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 'Mint' and clearly identifies the resource 'FREE Thisispaper Intelligence API key'. It distinguishes from sibling tools like fetch, search, etc. by focusing on key generation.

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 when to use the tool (to obtain an API key) and provides context on usage limits and key usage. It does not explicitly list alternatives, but the purpose is distinct from siblings, making the usage 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?

Annotations already declare readOnlyHint=true. Description adds value by listing returned fields (machine-written description, design language, details, dimensions, public URL), providing behavioral context beyond read-only nature.

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 sentence, front-loaded with purpose, every word adds value. No unnecessary fluff.

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 get-by-slug tool with no output schema and good annotations, description adequately covers purpose and return fields. Minor gap: no mention of error handling or performance, but acceptable for this 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% for the single slug parameter, which is self-explanatory. Description provides an example slug (audeum-kengo-kuma) for clarity but adds no additional constraints or format details.

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 states it returns full metadata for one project, including specific fields. Distinguishes from sibling tools like search_projects (search) and similar_projects (similar) by focusing on a single project identified by slug.

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?

Context signals suggest use when you have a specific project slug and need full metadata. While no explicit when-not, the sibling tool names (search, similar) imply alternatives for discovery.

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?

Annotations already declare readOnlyHint=true, indicating safe read operation. The description adds that results contain id, title, and url, but does not disclose pagination, sorting, or rate limits. Minimal additional behavioral context.

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 concise with two sentences, no fluff. It front-loads the core purpose and result format.

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 simple single-parameter input and read-only annotation, the description adequately covers the tool's behavior. It describes the resource scope and return fields, sufficient for basic usage.

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%; the schema already provides a description for the 'query' parameter with example. The tool description does not add further semantic detail beyond what the schema offers.

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 verb 'search' and the specific resource 'hand-curated architecture, design, photography and art projects from Thisispaper', and indicates the return fields. However, it does not differentiate from the sibling tool 'search_projects', leaving ambiguity.

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 on when to use this tool versus alternatives like 'search_projects' or 'similar_projects'. The description lacks context about appropriate use cases or conditions.

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?

Adds value beyond annotations: ranked summaries, specific return fields (name, studio, city, etc.), and API key limitation. Annotations declare readOnlyHint=true, which is consistent.

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 efficient sentences: first states purpose and output, second covers API key limitation. No wasted 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?

Complete for a search tool with two parameters. Covers data source, number of projects, return format, and authentication. Missing pagination info but not critical.

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. Description adds example search terms and output context, which aids understanding of the query parameter and the tool's function.

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?

Describes searching a specific curated collection (2,491 projects from Thisispaper) and returning ranked summaries with fields. Distinguishes from siblings like 'get_project' (single project) and 'fetch'.

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?

Provides context on API key cap (5 results without key, full with key). Does not explicitly state when to use vs alternatives, but context is clear enough.

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 discloses that results are precomputed (SigLIP neighbours), adding value beyond the readOnlyHint annotation. No destructive behavior is mentioned, which is consistent. However, it could elaborate on caching or result stability.

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 consists of two concise sentences with no fluff. Every sentence adds essential information: the purpose and the source of the input slug. It is front-loaded with the main function.

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?

While the purpose is clear, the description lacks information about the return format (e.g., fields like title, slug, or similarity scores). Without an output schema, the agent may need to guess the response structure. Adding a brief note on the output would improve completeness.

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?

Input schema coverage is 100%, so the description need not repeat parameter details. However, it adds context by recommending the slug from search_projects, which helps the agent provide correct input. This extra guidance raises the score above the baseline of 3.

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 finds nearest projects to a given slug using visual and semantic similarity (precomputed SigLIP neighbours). It specifies the verb (find nearest), resource (projects), and method, and distinguishes itself from siblings like search_projects and get_project by focusing on similarity.

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 clear context on when to use the tool: after obtaining a slug from search_projects results. It does not explicitly state when not to use it, but the purpose is sufficiently distinct from siblings (e.g., for exact project retrieval use get_project).

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