substack_publication_recommendations

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

With no annotations, the description carries the burden of behavioral disclosure. It correctly signals a read-only listing operation and explains that the result is a publication-to-publication graph. However, it does not describe pagination, limits, or whether the returned list is complete, which would help an agent reason about the response.

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 sentences with no filler. The core action is front-loaded, followed by return semantics, use-case context, and parameter provenance. Every sentence adds distinct value.

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 list tool with no output schema, the description is largely complete. It explains what is returned, why it is useful, and where the input id comes from. It would be more complete if it mentioned pagination or output shape, but nothing essential is missing for invoking the tool 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 coverage is 100% for publication_id, so the baseline is 3. The description adds meaningful provenance beyond the schema: it tells the agent that publication_id is 'the numeric id returned by /substack/publication, /substack/category, or /substack/user.' This helps an agent chain tools correctly.

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 publications one Substack publication recommends.' This clearly distinguishes it from sibling tools like substack_publication (details about a publication), substack_category (category listings), and substack_user_connections (user-level connections). The 'publication-to-publication graph' framing adds precise scope.

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?

Provides concrete usage context: it is 'useful for discovering publications beyond the 675-per-category ceiling on /substack/category.' This tells an agent when this tool is preferred over a close alternative, though it does not explicitly state when not to use it or name alternatives directly.

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