SageChimp book verdicts

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

With no annotations, the description carries the full burden, and it does disclose two real traits: only 'published' reviews are returned, and each carries an isArcReview flag for ARC/incentivized copies. It says nothing about authentication, rate limits, pagination, or how many results come back.

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 no filler, and the core action is front-loaded. It is appropriately sized for a straightforward read tool.

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?

There is no output schema and no annotations, so the description is the only documentation surface; it partially covers return content via the isArcReview flag but omits pagination behavior (limit defaults to 10, max 20) and the parameter-selection logic. Adequate but with clear 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?

Schema description coverage is only 67%, so the description should compensate, but it never mentions slug, limit, or query. The slug-vs-query fallback rule ('Title/author/ISBN if slug is unknown') lives only in the schema and their interaction is never explained.

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 ('Return') and resource ('published SageChimp reviews for a book'), which is unambiguous. It does not explicitly distinguish itself from the siblings get_book_verdict or search_books, so it falls short of the top tier.

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?

There is no when-to-use guidance, no mention of alternatives, and no prerequisites. Notably, the description never explains when an agent should supply 'slug' versus the title/author/ISBN 'query', which is the main decision the caller faces.

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 exist, so the description carries the full burden. It discloses the key behavioral rule (verdict requires 5 unpaid reviews; below that hasEnoughData is false and the sample is still returned), which is exactly the non-obvious behavior an agent needs. It doesn't mention auth, rate limits, or what a formal verdict looks like, so it's not fully exhaustive.

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 tight sentences: the core return, the invariant contents, and the verdict rule. Everything is front-loaded. Slightly terse on the interaction between slug and query, but no wasted text.

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 2-param, no-annotation, no-output-schema tool, the description covers the critical verdict threshold and fallback behavior. It omits output structure details (what 'verdict' looks like) but for a read tool that's a minor gap and the behavioral rule is the most important omission to have filled.

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%, documenting both slug and query with examples, and the description adds no parameter syntax beyond that. The description does specify the output semantics (hasEnoughData) but not the relationship between the two params' fallback behavior, so it lands at the 3 baseline.

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 precise verb (Return), the exact resource (SageChimp catalog context and unpaid-vs-ARC verdict), and enumerates the payload (catalog facts, series, comparable titles, unpaid reviews). This clearly distinguishes it from siblings get_book_reviews (reviews only) and search_books (discovery).

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 it: when a catalog-plus-verdict view is needed, with a concrete threshold (5 unpaid reviews) that tells the agent what 'enough data' means. It doesn't explicitly name when to prefer get_book_reviews or search_books, so it falls short of a 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?

No annotations are provided, so the description must carry the behavioral burden. It discloses the discovery/entry-point role but says nothing about result ordering, matching strategy (substring vs exact), empty-result behavior, or rate limits. Adequate but with clear 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?

Two short sentences with no redundancy, and the workflow hint ('use this first') is front-loaded immediately after the capability statement.

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?

Covers what the tool searches, which fields, and when to reach for it – enough for an agent to invoke it correctly. Missing only minor behavioral details (result ordering, partial matching, empty results) that would round it out.

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 only 50% (limit is undocumented in the schema), and the description partially compensates by naming the four accepted query flavors. It still does not clarify limit semantics or max value, so it does not fully fill the coverage gap.

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?

Names the specific catalog (SageChimp) and the searchable fields (title, author, slug, ISBN), so the resource and verb are unambiguous. It is clearly distinguished from the sibling tools, which deal with reviews and verdicts rather than discovery.

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?

Explicitly states 'Use this first when the user names a book but you do not have a slug' – a clear entry-point condition. It implies downstream alternatives (get_book_reviews, get_book_verdict) without naming or excluding them, so it stops just short of a full when/when-not.

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