Mano DeAyala AI Gateway

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and side-effect behavior. The description adds that the tool returns full text and expects a search-derived id, but it does not disclose additional behavior beyond what structured annotations already provide.

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 one concise, front-loaded sentence. It communicates the action, the resource, and the input source without any filler or redundancy.

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 an output schema and annotations covering safety and idempotency, the description is nearly complete. The only notable gap is the lack of differentiation from the sibling 'get_article', which could create mild selection ambiguity.

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%, with the 'id' parameter already described as 'Document id from search results'. The description similarly mentions the id comes from search, but adds no further semantic detail beyond the schema, so the baseline score of 3 applies.

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 states a specific verb ('Retrieve'), resource ('full text of one document'), and input ('id returned from search'). It clearly distinguishes from search tools, but it does not differentiate from the sibling 'get_article', which may also fetch a document by 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 the correct usage sequence: run 'search' first, then use the returned id to fetch the document. However, it does not explicitly state when to choose this tool over the sibling 'get_article' or 'search_articles', so guidance on alternatives is missing.

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 establish readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context by specifying the output is 'full clean text' and explaining how a slug maps to a URL segment, going beyond the structured 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?

A single, focused sentence that leads with the core behavior and immediately clarifies the identifier format. No filler or redundant restating of the tool name.

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, read-only tool with annotations and an output schema, the description covers what the tool does and how the parameter is derived. Nothing essential is missing 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?

Schema coverage is 100% and the schema already gives an example. The description supplements this by explicitly defining a slug as 'the last path segment of an article URL', which clarifies the expected format and makes correct invocation easier.

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 a specific action ('Fetch the full clean text of one article') on a specific resource identified by slug. The phrase 'full clean text' distinguishes it from generic URL fetching and from list/search siblings that return multiple or partial results.

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 the tool is for retrieving one article when you already have its slug, and the sibling names suggest alternatives like listing or searching. However, it does not explicitly state when not to use this tool or name an alternative, leaving usage partially to inference.

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 cover safety (readOnly, idempotent, non-destructive). The description adds behavioral context beyond that: results are limited to recent publication and scoped to this publication. No hidden side effects or surprising behavior are hinted at, which is fine given the 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?

One sentence conveys verb, resource, ordering, and scope with zero filler. The most important information is front-loaded.

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 tool with one optional parameter, an output schema, and rich annotations, the description is complete enough for an agent to invoke it correctly. No critical details are missing.

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 description coverage for the single limit parameter, the schema already documents the parameter. The description does not add parameter-level detail, so the 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 states a clear verb ('List'), resource ('articles'), and ordering ('most recently published'), and scopes to 'this publication.' It is semantically distinguishable from siblings like popular_content and search_articles, though it does not explicitly name them.

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 intended use case—retrieving recent articles—is implied by the wording, so an agent can infer when to call it. However, it gives no explicit guidance about when to prefer it over popular_content or search_articles, and no exclusions.

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 annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds useful context by explaining the popularity ranking is based on actual AI-assistant fetches, but it does not disclose further behavioral details such as pagination behavior or response shape. This is acceptable given the annotations and output schema.

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 with no filler: the first states what the tool returns and how ranking works, the second gives concrete query phrases for when to use it. Every sentence earns its place.

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 tool with two optional fully-documented parameters, complete annotations, and an output schema, the description is sufficient. Nothing essential is missing 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?

Schema description coverage is 100%, with days and limit both fully described including defaults and bounds. The description does not add parameter-level detail, but it does not need to because the schema already carries that information. 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 clearly identifies the tool as returning most-read or most-requested articles, with a specific ranking criterion: how often AI assistants have actually fetched them. This is a specific verb+resource+ranking definition that makes it easy to distinguish from siblings like search_articles or list_recent_articles.

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 explicitly gives concrete use cases: 'what is your most popular article', 'top reads', or recommending what to read. It does not mention when not to use it or name alternatives, but the clear context is sufficient for an agent to select it appropriately.

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 establish read-only, idempotent, and non-destructive behavior. The description adds valuable behavioral context by clarifying that results are documents with id/title/url and that full text is deliberately not returned here—routing the agent to 'fetch' instead. This goes beyond what the annotations state.

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 short sentences, each earning its place. The core action is front-loaded, return behavior is stated, and the follow-up action to 'fetch' is included without unnecessary detail.

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 read-only annotations and an output schema, the description is mostly complete: it states what is returned and how to get full text via 'fetch'. The only notable gap is the lack of explicit disambiguation from 'search_articles', but the low complexity keeps this from being a major omission.

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 schema already documents 'query' as a search query. The description does not add much semantic detail beyond that, but it does frame the query as a search over site content. This matches the baseline for high schema 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 a specific action ('Search this site's content') and the resource being searched, and adds what is returned (matching documents with id, title, url). It mentions the relationship to 'fetch', but does not explicitly distinguish itself from the sibling 'search_articles', so sibling differentiation is incomplete.

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 when to use the tool: when you need to search site content. It also gives a useful next-step instruction ('pass an id to fetch for the full text'). However, it provides no explicit when-not-to-use guidance or comparison to the closely related sibling 'search_articles'.

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, idempotentHint, and destructiveHint, so the description need not restate safety. It adds useful context by mentioning 'best-matching' and the returned fields, but it does not disclose ranking behavior or pagination details beyond what the schema already provides.

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 short sentences with no filler. The core operation is front-loaded and the return details are concise, making it easy for an agent to parse quickly.

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 2-parameter schema, complete schema descriptions, rich annotations, and presence of an output schema, the description is fully sufficient for an agent to select and invoke the tool correctly. No critical information is missing.

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%, with both 'query' and 'limit' already documented. The description only reinforces 'by keyword' and adds no meaningful semantic detail beyond the input 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 states a specific verb ('Search'), resource ('this publication's articles'), and method ('by keyword'), and enumerates return fields. It clearly communicates what the tool does, though it does not explicitly differentiate it from sibling tools like 'search' or 'get_article'.

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 when to use this tool (when keyword search over articles is needed), but it offers no explicit exclusions or references to alternatives among the sibling tools. Usage guidance is left largely to inference.

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