WildRun AI

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

Annotations already cover readOnly, idempotent, non-destructive and closed-world, so the safety profile is done. The description adds genuinely new behavior context: the return format is Markdown and the payload is roughly a third the size of the HTML page, which helps an agent reason about context budget.

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 is returned and in what format, with the slug-source hint trailing. No filler.

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 single-parameter read with no output schema, the description covers format, size profile and slug sourcing, which is sufficient to call correctly. It does not mention behavior for a missing or unknown slug, a minor remaining gap.

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 already documents the slug pattern with an example. The description adds value beyond the schema by telling the agent where to obtain valid slugs, which the schema cannot express.

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 ('full text of one article as Markdown') plus the keying parameter (slug). The parenthetical pointing to list_articles distinguishes it cleanly from that sibling, which enumerates rather than returns content.

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 routes the agent to list_articles as the source of valid slugs, which is a concrete alternative/precedence signal. It does not spell out when not to use it (e.g. for excerpts or search), so it stops short of full when/when-not coverage.

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 openWorldHint=false, so the safety profile is fully covered. The description adds one genuine behavioral detail beyond that — page URLs also honor 'Accept: text/markdown' content negotiation — but says nothing about response shape, size, or whether multiple pages are returned.

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 the resource identity front-loaded and the content attributes trailing. It is slightly run-on and carries marketing framing ('WildRun AI's one service'), but no sentence is pure padding.

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 parameterless, read-only content fetch with no output schema, the description tells the agent what the returned content covers and how it can be retrieved (markdown negotiation). Annotations cover the safety profile, so nothing essential 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 and the schema is a closed empty object, so there is nothing for the description to disambiguate. Baseline 4 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 enumerates what the resource contains (page, scope-and-pricing section, free audit request, contact page) but never states the action — there is no verb like 'returns' or 'retrieves'. It is distinguishable from get_article/list_articles only by subject matter (service lines vs. articles), not by an explicit scope statement.

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 guidance on when to call this versus get_article or list_articles, and no mention of prerequisites or exclusions. The only usage-adjacent line — 'Managed work is scoped and quoted after the free audit' — is content context, not a selection rule.

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 (read-only, idempotent, non-destructive, closed-world), so the description does not need to repeat that. It adds useful behavioral context by stating the archive is ordered newest first and by listing the returned fields, which helps the agent understand the response shape even without an 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?

The description is two tightly written sentences with no waste. The core resource description and the key usage instruction are both 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?

For a simple read-only list tool with two optional parameters and no output schema, the description supplies the essential return fields, ordering, and usage guidance. Combined with the annotations and fully described schema, an agent has enough information 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?

Schema description coverage is 100%, so both parameters are already fully documented in the schema. The description does not add syntax, defaults, or filtering semantics beyond what the schema provides, which is the expected baseline when the schema carries the parameter documentation.

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 identifies the resource as the archive of published articles, states the ordering as newest first, and lists the fields returned. It also distinguishes the tool from get_article by positioning this as the discovery step before fetching a specific article.

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?

It explicitly says to use this tool to find something to read before calling get_article, giving a clear usage context and naming the relevant alternative. It does not describe exclusions or when not to use it, but the primary routing guidance is present.

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