listme.name rankings

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds useful output-shape context ('plain-language differences', 'rank, score and verdict'), but says nothing about behavior when a product is missing from rankings or when the two products don't share any ranking.

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 dense sentence that front-loads the core output ('two products side by side') and then enumerates what's returned. No filler, nothing redundant.

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?

A low-complexity two-param read tool with full annotations and no output schema. The description conveys the response shape well enough to call correctly. Minor gap: no signal on behavior when rankings are missing or when the slugs don't resolve.

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% and both params are documented with pattern and 'product slug' semantics. The description adds no parameter-level detail beyond the schema. 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 ('compare') and resource ('products') with concrete scope: 'facts, plain-language differences, and the rank, score and verdict each gets in every ranking both appear in.' This content-level specificity distinguishes it from get_product (single lookup) and find_alternatives without needing to 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 scope ('every ranking both appear in') implies this is for pairwise comparison, but it never says when to prefer compare_products over calling get_product twice or find_alternatives. No explicit when/when-not or alternative named.

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 a safe read (readOnlyHint=true, destructiveHint=false, idempotentHint=true), so the bar is lower. The description still adds genuine behavioral value by disclosing result ordering ('best first') and that each result carries an explanatory rationale, which matters because there is no 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 compact sentences with the core result contract front-loaded and no filler. The opening is a noun fragment rather than a full statement of action, which slightly weakens the lead.

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 5-parameter, read-only tool with no output schema, the description does cover result ordering and content, but it omits how 'limit' behaves and what 'share a ranking' means precisely. It is adequate without being 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 60%, and the description loosely maps to free_only, open_source_only and platform ('free, open-source or a platform'). It adds no detail beyond that, leaving 'limit' and the meaning of platform support entirely to the schema; a baseline 3 is appropriate at this coverage level.

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 resource and scope: products that share a ranking with a given product, returned best-first with a rationale. It is distinguishable from siblings like get_product or search_catalog, though it never explicitly names an alternative or states a verb like 'find'.

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 and no comparison against siblings such as compare_products or search_catalog, which an agent could plausibly confuse with this tool. The only contextual clause ('Can be restricted to free, open-source or a platform') describes filtering options, not tool selection.

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, destructiveHint=false and a closed world, so safety behavior needs no restating. The description earns credit by disclosing what the call actually returns — an aggregated fact sheet including ranking memberships and top alternatives — which is meaningful content since there is no output schema. It stops short of describing response shape, size, or failure behavior for an unknown slug.

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 dense sentence, front-loaded with the resource scope and then the returned fields. Nothing is padded, though the trailing enumeration is long enough to read as a field list rather than a crisp scope 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?

With no output schema, the description must carry the return-value burden, and it does so thoroughly by listing the categories of facts returned. The main remaining gap is the absence of guidance on how this differs from the ranking/alternative siblings, which matters given the overlapping content.

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 is a single parameter with 100% schema description coverage, and the schema already specifies the slug pattern and that it comes from search_catalog or a ranking. The description adds no further meaning about the product parameter, so 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 names the exact resource (one product/book) and enumerates the specific facts returned — pricing model, platforms, open-source status, strengths, limits, rankings, alternatives — which is far more specific than a tautological restatement of the name. It only partially distinguishes itself from siblings, since 'every ranking it appears in' and 'top alternatives' overlap conceptually with get_ranking and find_alternatives without explaining the boundary.

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?

Usage is only implied: the fact that it returns a single product's detail implies a lookup use case, and the schema note that the slug comes from search_catalog or a ranking hints at the workflow. There is no explicit when-to-use, no statement of when to prefer compare_products or find_alternatives, and no prerequisites or 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?

Annotations already establish the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar for additional disclosure is lower. The description earns credit by disclosing the shape of the read result in detail (criteria, ranking entries, 0-100 editorial score, best-for, key facts), which is genuinely useful since no output schema exists. It does not mention pagination, truncation, or behavior when a filter matches nothing.

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 wasted words: the first front-loads what the tool returns, the second states the optional narrowing. Everything is load-bearing and easy to scan.

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 properly compensates by enumerating the return contents, and annotations cover the safety profile, making this largely complete for a two-parameter read tool. The remaining gap is guidance on obtaining the 'list' slug and on filter-miss behavior, neither of which is addressed.

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 both parameters are already documented in the schema, and the description's filter examples (free, open-source, linux) merely restate the schema's own enumeration. Baseline 3 is appropriate since the schema carries the semantics rather than the description.

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 gives a specific verb-and-resource ('One ranked list') and enumerates its payload (criteria, how to choose, every entry with rank, editorial score, verdict, best-for, key facts), which is far more concrete than a tautology. It does not name a sibling, so an agent must infer the boundary against list_rankings (which enumerates available lists) and get_product on its own.

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?

Usage is only implied: an agent can deduce that it needs a list slug and that a filter is optional, but the description never states when to reach for this tool versus list_rankings, search_catalog, or get_product. It also omits that the slug must come from list_rankings/search_catalog, information that lives only in the schema.

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 the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=false), so the bar is lower. The description nonetheless adds real value by disclosing the return shape in both modes (category list counts vs. ranked lists with top picks), which matters because there is no 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 clauses, zero filler, and the mode-switching condition is front-loaded so the agent can decide before reading further. Every word 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?

With no output schema, the description carries the return-value burden and does describe what each mode returns at a useful level. It omits ordering, ranking criteria, and result-size/limit behavior, which a caller might want, but nothing needed to invoke the tool correctly 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%: the single category parameter already has a pattern and a worked example ('security-privacy'). The description adds only the semantic consequence of supplying it, not format or constraint detail, 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+resource (list rankings) and precisely describes two distinct output modes keyed on the optional argument, so an agent knows exactly what it gets. However, it never differentiates itself from the sibling get_ranking, which presumably returns a single ranking, leaving that disambiguation to inference.

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 'Without arguments / With a category slug' construction is effectively usage guidance: it tells the agent when to omit vs. supply the parameter and what each choice yields. It stops short of naming alternatives or exclusions (e.g., 'use get_ranking for a single list'), so it is clear context without routing rules.

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 readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds genuinely new behavioral context by disclosing what the call returns (slugs for downstream tools, page URLs for citation), which is valuable since no output schema exists. It stops short of describing pagination or limit behavior.

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 zero filler; the purpose is front-loaded and the return-value note follows. Every clause 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?

With no output schema, the description carries the return-value burden and does so at a high level (slugs, page URLs). What is missing is guidance on result limits/truncation and how to narrow results when the query is broad, which an agent would benefit from.

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 67%: query and type are documented in-schema, while limit has no description anywhere. The description's "by name or topic" only loosely reinforces the query parameter and adds no format or syntax detail beyond the schema examples. 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?

States a specific verb (Find) and enumerates the resources it covers (rankings, products, books, categories, articles), plus the discovery role it plays by returning slugs for other tools. It does not explicitly distinguish itself from the search-adjacent siblings like list_rankings, so it stops 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?

"Returns slugs to pass to the other tools" implies this is the entry point before get_product/get_ranking/compare_products, which is useful implicit routing. However, there is no explicit when-to-use vs list_rankings or find_alternatives, and no stated exclusions.

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