Agentic Weekly

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered structurally. The description adds genuinely useful context by defining the accepted input domain (tool slugs or model slugs) and pointing at /tools.json and /models.json. It does not say what the comparison produces or whether mixing types is allowed, so it adds some but not rich behavioral context.

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 filler, and the core action is front-loaded ahead of the input-domain clarification. Every clause adds information an agent needs.

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 was not required to explain return values, but for a comparison tool it omits which attributes get compared and whether a and b must be the same kind of entity. For a two-parameter tool with zero schema coverage, these are meaningful gaps rather than trivial ones.

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 0% — both parameters are bare strings named 'a' and 'b' with no descriptions — so the description carries the full burden and largely succeeds by explaining that each value is a tool slug or a model slug and where to find valid slugs. It falls short of explaining whether a and b may reference different entity types or whether order matters.

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 a specific verb (compare) and states the inputs are two items from the catalog, then clarifies those items may be tool slugs or model slugs. It distinguishes itself from retrieval siblings like get_model or latest_models, though 'items from our data' is vague until the second sentence clarifies.

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 infer this is for side-by-side comparison rather than lookup, and the slug references hint at where to obtain valid inputs. There is no explicit statement of when to prefer this over get_model or latest_models, and no note on whether the two arguments must be of the same kind.

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 (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description goes beyond them by disclosing what comes back — a per-fact source URL, as-of date and Reported/Tested label — which tells the agent the response carries provenance and trust metadata.

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 sentence with no filler; the identification mode (slug or exact name) comes first and the return-shape detail follows, so it is well 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?

With no output schema, the description rightly spends its words on the returned fields, and one-parameter input is fully covered by the schema. Minor gaps remain: nothing about behavior when the slug is unknown or whether name matching is case-sensitive.

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%, so the schema already defines the single slug parameter. The description adds value by giving a concrete example value ('gemini-4-argon') and clarifying that either a slug or an exact name is accepted, which helps an agent construct a valid value.

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 ('Get') and resource ('one model') and makes the singular, identifier-based lookup explicit, which separates it in spirit from sibling list tools. It stops short of naming those siblings, so differentiation is inferable rather than stated.

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: 'Get one model by slug' suggests looking up a specific known model rather than browsing or comparing. There is no explicit when-to-use vs latest_models/compare_tools guidance and no exclusion conditions.

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, closed-world behavior, so the safety profile is covered. The description adds genuine context beyond that: results are sourced facts with provenance and a 'last-verified date', and ordering is 'Newest first' — both material to how an agent should trust and present the data.

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, zero waste. The returned-field list and sort order are packed into one clause and the leading verb carries the purpose immediately.

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 usefully enumerates the return fields, and it discloses sort order and data provenance. The remaining gap is filter semantics — how group/vendor/category interact or whether they combine — which an agent would have to discover empirically.

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 75%; group, vendor, and category are documented in the schema, while limit has only a default/bounds. The description says nothing about any parameter, so it neither compensates for the undocumented limit semantics nor enriches the filter behavior. Baseline 3 is correct 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?

States a specific verb and resource ('List the newest AI models') and enumerates the fields returned, so the agent knows exactly what it gets back. It does not, however, distinguish itself from the sibling latest_releases, which reads as a near-synonym.

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 use this versus latest_releases, get_model, or compare_tools — the most likely confusion points given the sibling set. The agent must infer that this is a browse/list tool and the others are lookup/compare tools.

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 this a read-only, idempotent, closed-world, non-destructive operation, so the safety profile needs no restatement. The description does add real value by disclosing that both first-seen and source-published timestamps are returned and that they are in UTC, but says nothing about ordering, recency window, or how the default result count behaves.

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 source and timestamp facts are packed efficiently. It is dense but every clause carries information.

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 well to sketch the return content (briefs plus two timestamp kinds in UTC). However, for a parameterized feed tool it omits what 'latest' means in practice (recency window, sort order) and what the limit controls, leaving meaningful 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?

There is one parameter and schema description coverage is 0%, so the description carries the full burden of explaining 'limit' — yet it never mentions it, its default of 10, or the 1–50 range. An agent must open the schema to learn anything about result sizing.

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 specific resource (AI tool release news briefs) and its origin (Agentic Weekly), so the agent knows this is a news-feed retrieval rather than a model lookup. It implicitly distinguishes itself from latest_models by scoping to 'tool releases', but never names the sibling 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?

Usage is only implied: an agent can infer this is the tool for latest release news, but there is no statement of when to prefer it over latest_models or compare_tools, and no prerequisites or exclusions. Nothing is misleading, but routing decisions are left to inference.

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