Read one published Chinese, English, Thai, or Japanese Kaucim reference article as Markdown by providing its language and slug; unknown slugs return an error.
Read one published Chinese, English, Thai or Japanese article as Markdown. Use a known article slug from the site. An unknown slug returns an error.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | Yes | ||
| slug | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: the payload is rendered as Markdown and an unknown slug fails with an error rather than returning empty results.
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 short sentences, no filler, front-loaded with what is read and how it is returned before the slug precondition and the failure mode. Nothing is 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?
There is no output schema, so the description correctly covers the return format (Markdown) and the error case. Combined with rich annotations, an agent has enough to call this tool correctly; only slug validation details are left solely to the schema.
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 0%, so the description must carry the load, and it partly does: it expands the lang enum into the four human-readable languages and frames slug as a known site article identifier. It does not, however, describe the slug format constraints (lowercase hyphenated, max 100 chars) that the schema pattern enforces.
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 (Read), a specific resource (one published article), a scope (Chinese, English, Thai or Japanese) and a return format (Markdown). The resource is clearly distinct from the sibling tools (reference sources, product catalog, stick), though no sibling is named 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?
"Use a known article slug from the site" gives a precondition, and the error-on-unknown-slug note helps, but there is no explicit when-to-use versus an alternative or discovery path for when the slug is not known. Usage is implied rather than prescribed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.