List first-party essays

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so safety is well covered. The description adds behavioral context beyond annotations by stating the full scope ('every long-form essay') and the kind of output ('citable canonical URLs'). This is useful and non-redundant, though it doesn't discuss pagination or rate limits—minor given the read-only idempotent nature.

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 zero filler: the first states the core function and return fields, the second gives usage routing. The key information is front-loaded, and every sentence 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?

For a simple read-only list tool with one optional parameter and an output schema, the description fully covers what, where, and when to use it. It even names the alternative tool for a different use case. No critical information 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%, so the locale parameter is fully documented in the schema (enum and meaning). The description does not add further parameter semantics beyond what the schema already provides, which fits the baseline of 3.

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 ('List') and identifies a concrete resource ('every long-form essay published on articles.santismm.com') along with the data returned (language, dates, topics, canonical URLs). It clearly distinguishes itself from the sibling 'search_articles' by contrast, so an agent can tell them apart immediately.

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?

Explicit usage guidance is provided: 'Use this to browse the essay catalogue; use `search_articles` when you have a topic rather than a slug.' This tells the agent both when to use this tool and when to prefer the alternative, leaving no ambiguity about selection.

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