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

No annotations are provided, so the description carries the full behavioral burden. 'Retrieve' implies a read-only, low-risk operation, but it says nothing about behavior on a missing/invalid path, content size limits, or how the 'summary' format truncates output (only the schema mentions the 500-word cut).

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 tight sentences with the core action front-loaded and the usage hint second; no filler or restatement of the title.

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 two-parameter read tool with no output schema, the description covers the essential call pattern and path format. It could add a line about the markdown-vs-summary output choice, but the schema already documents it.

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 echoes the path format already documented in the schema and adds no new meaning about the 'format' enum or its effect on returned content.

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?

States a specific verb and resource: 'Retrieve a full research article by its path.' The word 'full' usefully distinguishes it from summary/search siblings, and the reference to paths from search results implicitly separates it from search_research, though no sibling is named explicitly.

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?

Gives clear usage context: take the path from search results, or supply a relative path, with a concrete example. It does not state when NOT to use it (e.g., prefer search_research to discover articles, or get_latest_research for new items), so it stops short of full routing 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 discloses the recency sort, but says nothing about return format, ordering tie-breaks, pagination, or whether count is capped server-side (the cap lives only in the schema). For a read tool with zero annotation coverage this is thin.

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 with no filler; the scope qualifier ('across all categories') is placed where it reads naturally. It is efficient, though it is arguably too terse to be maximally useful.

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 must stand alone, and it covers purpose and sort order but omits return shape and any behavioral caveats. Adequate as a minimum-viable definition, but gaps remain for a tool agents must select over search_research.

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%: both 'count' (default 5, max 20) and 'category' are documented in the schema. The description adds no extra meaning about the category filter, e.g. whether it accepts top-level names only, so the baseline 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?

States a specific verb ('Get') and resource ('recently updated research articles') plus scope ('across all categories'). It distinguishes itself from search_research by implying recency ordering, but never names the sibling to make the distinction explicit.

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 choose this over search_research, which is the obvious alternative for retrieving articles. The one hint is 'most recently updated', which implies a recency feed, but no conditions or exclusions are stated.

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 disclosure burden. It does describe what the call returns (the complete category hierarchy plus URLs), but says nothing about response size, caching, or depth limits for what is likely a large tree. For a zero-parameter read tool the risk is low, so this is adequate but thin.

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 zero waste, front-loading the resource and following with the payload contents and purpose. Nothing is padded or repeated.

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 must explain the return value, and it does so (categories, subcategories, page URLs). It falls just short of full completeness by omitting any hint of tree size or traversal cost, but an agent has enough to call 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 tool takes no parameters (empty schema, 100% coverage), so the baseline of 4 applies. There are no parameter semantics to clarify or compensate for.

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?

States a specific verb and resource ('Get the full hierarchical topic tree') and enumerates the returned content: categories, subcategories, and their page URLs. The word 'hierarchical' implicitly distinguishes it from the flat list_categories sibling, but the contrast is never made explicit.

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 sentence 'Use this to understand the site structure' gives a general context for use, which is more than nothing. However, it never names list_categories or search_research as alternatives, nor states when this tool should be avoided, leaving the routing decision 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?

No annotations are provided, so the description carries the burden. 'List' implies a safe read operation and the mention of article counts hints at the return content, but nothing is said about ordering, nesting, or whether counts are live or cached. Adequate but thin for a tool with zero annotation coverage.

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, front-loaded with what the tool returns and followed by the usage cue. No 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 zero-parameter, no-annotation, no-output-schema tool, the description covers what is returned (categories, subcategories, counts) and why to call it. It could clarify the return shape (flat vs nested) or ordering, but nothing essential to invocation 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. No misleading parameter claims are made.

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?

States a specific verb and resource ('List all research categories and subcategories') and adds scope detail via 'with article counts'. It does not explicitly differentiate itself from the sibling get_topic_tree, which sounds closely related, so it falls short of a 5.

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?

'Use this to understand what's available before searching' gives a clear use context and implies the workflow position relative to search_research. It stops short of naming an alternative tool or stating when not to use it, so 4 rather than 5.

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 behavioral burden. It usefully discloses the return shape ('ranked results with titles, summaries, and article paths'), which goes beyond structured data. However, it says nothing about pagination, ranking logic, corpus limits, or auth requirements, leaving substantial gaps for a search tool.

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?

Three short sentences, front-loaded with the core action before return format and usage. No filler, though it is slightly padded by the generic closing usage line.

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 three-parameter search tool with complete schema coverage, the description covers purpose, output fields, and general usage. Missing sibling differentiation and any behavioral caveats, but nothing critical blocks correct invocation.

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, category values, and the maxResults default/ceiling. The description adds no parameter meaning beyond what the schema provides, which is the baseline-3 case.

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 names a specific verb and resource: 'Full-text search across Grandpa's AI research corpus.' That is clearly distinct from retrieval siblings like get_article and get_latest_research. It stops short of explicitly contrasting itself with those siblings, so it lands at 4 rather than 5.

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?

'Use this to find research on any topic' implies the usage context but never states when NOT to use it or when to prefer get_article, get_latest_research, or get_topic_tree. Sibling routing is left entirely to inference.

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