Agent Papers

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 reveals the output structure (comparison matrix with common and category-specific fields) and implies a read operation, but it does not disclose any limitations, response size, or whether data is live or cached. It is adequate but not rich.

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 front-loads the action and output. Every word contributes value, with no filler or repetition.

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?

This is a simple tool with one enum-constrained parameter and no output schema. The description explains the purpose and output shape sufficiently for the tool's low complexity, though it could mention return format or category-specific behavior for 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?

Schema coverage is 100%: the only parameter 'category' has a clear enum list and a description 'Category id to compare.' The tool description does not add additional meaning beyond what the schema already provides, 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?

The description uses a specific verb 'Return' and defines the resource as 'a comparison matrix for one category,' clearly distinguishing it from sibling tools like search or get_company. It also specifies the output content (common fields and buyer-relevant category fields), leaving no doubt about the tool's 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 for a single category and mentions it returns a comparison matrix, but it does not explicitly state when to choose this over alternatives or provide exclusionary guidance. Context is clear enough, yet no direct 'when-to-use vs. not' is offered.

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 were provided, so the description carries the burden. It discloses the kind of content returned (offerings, sources, freshness, category-specific facts) and implies a read-only fetch. However, it does not elaborate on error behavior, authentication, or pagination, which leaves some gaps.

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, well-structured sentence that front-loads the core action and resource, then lists included contents. 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?

With no output schema, the description does a good job of conveying what the entry contains. It clearly defines the scope ('one full company entry') and lists key data categories. It could mention error handling or what happens if the slug is invalid, but for a simple fetch tool it is largely complete.

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 sole parameter 'slug' is already described with an example. The description adds no additional parameter-specific semantics beyond what the schema provides, 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 clearly states the verb 'Fetch' and the resource 'one full Agent Papers company entry', and enumerates what it includes. This distinguishes it from sibling tools like search (which likely returns multiple results) and compare (which compares entries).

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 for retrieving a single company's full details by saying 'one full company entry'. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to select it when a single full record is needed.

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 core behavior (returning field names and reasons) and the conditional scope (full vs. category). It does not mention error handling, response format, or any side effects, but for a read-only schema retrieval tool this is minimally adequate.

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, front-loaded with the key action, and no filler words. Every phrase contributes information: what is returned, the format (field names + reasons), and the optional scope.

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 tool with a single optional parameter and no output schema, the description covers the essential behavior and parameter effect. It is complete enough for an agent to select and invoke correctly. Slightly more detail about return structure or defaults could push it to 5, but not necessary.

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 describes the category parameter only as 'Optional category id.' The description adds meaning by explaining that omitting it returns the full schema and including it returns one category's schema. This clarifies the parameter's role beyond the schema's brief label.

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 ('full registry schema or one category'). It distinguishes itself from sibling tools like get_company (which returns company data) and list_categories (which lists categories) by focusing on schema metadata with field names and buyer reasons.

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 'full registry schema or one category' implies the optional category parameter and suggests when to use this tool (when you need schema structure). However, it does not explicitly state when not to use it or mention any alternative tools (e.g., list_categories for just category names). Usage guidance is implied but not explicit.

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 clarifies that the tool returns categories with counts and descriptions (implying a safe read-only operation), but it does not detail response structure, ordering, or any limitations. This is acceptable for a simple list tool but adds no depth beyond the immediate outcome.

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 sentence that is front-loaded with the action ('Return every Agent Papers category') and immediately provides value (counts and descriptions). 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 zero-parameter, list-only tool with no output schema, the description fully covers what it does, what it returns, and why it might be used. It is complete without needing to explain return values or side effects.

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, making schema coverage trivially 100%. The description does not need to elaborate on parameter meanings, and the baseline for zero-parameter tools is 4. No additional semantics are necessary.

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' with resource 'every Agent Papers category with counts and short descriptions,' making the tool's function unmistakable. It also ties the purpose to choosing the right comparison surface, which distinguishes it from sibling tools like search or get_company.

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 'so an agent can choose the right comparison surface' explicitly indicates when to use this tool (before selecting a comparison). However, it does not name alternative tools or state when not to use it, so it stops short of full exclusion 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 that it matches name/tagline, supports filters, and returns 'compact vendor records for ranking,' which is useful behavioral information. However, it omits details like pagination, result limits, ordering, or what happens when no match is found, leaving some behavioral ambiguity.

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, each earning its place. The first states the action and scope, the second describes the output. No redundant or filler content.

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, the description should explain return values more thoroughly. It says 'compact vendor records for ranking' but does not specify the record structure or whether multiple results are returned. The input parameters are well covered, but the output side is vague, leaving the description incomplete for a fully self-sufficient 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 description coverage is 100%, so the baseline is 3. The description adds minor context by explicitly tying the query to name/tagline and the optionality of category and status, but these are largely already in the schema descriptions. No significant new parameter semantics are introduced.

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 ('Search') and identifies the resource ('Agent Papers companies') plus the searchable fields ('by name or tagline'). It clearly distinguishes from sibling tools like get_company by focusing on search-based discovery rather than exact retrieval.

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 gives clear context: use this when looking up companies by name/tagline, with optional category and status filters. It does not explicitly mention alternatives or exclusions, but the scope is unambiguous and appropriately set within the sibling tool suite.

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 the full behavioral burden. It explains that entries are 'derived from registry added and updated dates,' which gives some insight into how the tool works. However, it does not disclose return format, pagination, or potential side effects, leaving gaps in 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?

The description is a single, concise sentence that front-loads the main purpose. Every word adds value with no unnecessary fluff or repetition.

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 optional parameter and no output schema, the description adequately conveys what it returns and how entries are derived. It could enrich the return format details, but given the low complexity, it is fairly complete.

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 fully describes the single parameter 'since' with 'Optional inclusive YYYY-MM-DD lower bound.' The description adds no extra meaning beyond what the schema already provides, so with 100% schema coverage the baseline 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 uses a specific verb 'Return' and clearly identifies the resource as 'changelog entries derived from registry added and updated dates.' It also mentions optional date filtering, which distinguishes it from sibling tools like compare or search. This is unambiguous and distinct.

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 for when to use the tool by defining its output (changelog entries) and the optional date filter. It does not explicitly name alternatives or exclusions, but the purpose is self-evident and distinct from sibling tools, making the usage context reasonably clear.

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