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

The description discloses behaviors not covered by annotations: deep-heading matches auto-prepend H2 parent intro, calling with no `heading` on data tables lists top-level keys, and 404 responses include available headings + cross-file hints. It also clarifies path validation (learning:N vs learnings/<slug>.md). These are significant behavioral details.

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 dense and front-loaded with the core action, then systematically covers usage scenarios, exclusions, and special cases. It is somewhat long, but every sentence contributes crucial context for a tool with many nuanced behaviors, making it appropriately structured.

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 states the return (markdown) and error behavior (404 headings/hints). It also addresses special cases (data tables, community findings) and explains how to use headings for sections. This is a complete reference for the tool's complexity.

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?

Although the schema has 100% parameter coverage, the description enriches both parameters. It explains that `path` should be used verbatim from other tools, and `heading` supports breadcrumbs, leaf-only, case-insensitive fuzzy matching, plus special behavior for keyed catalogs. This goes far beyond the schema's basic descriptions.

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 opens with a specific verb and resource: 'Fetch full markdown of a doc by `path`'. It specifies the document types and return format, and distinguishes itself from siblings like `lookup_native` and `grep_docs` by stating what it is NOT for. This provides unambiguous purpose.

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 'Use to retrieve full content after a search snippet looks promising' gives a clear trigger. It repeatedly states when to prefer alternatives ('For individual script natives prefer `lookup_native`', 'For code symbols (`addItem`) use `grep_docs`') and even explains special handling for data tables and community findings. This is exemplary usage guidance.

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