hyperfeed_subscribe

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does mention that re-calling is safe ('safe to call again to refine') and describes the semantics of fields (e.g., `interests` as standing topic hints). However, it does not disclose what the tool returns, whether it overwrites previous settings, or if any side effects (like triggering a digest) occur. This is moderately transparent but lacks critical operational 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 concise and well-structured, using a single paragraph that front-loads the purpose, then lists each parameter with backtick formatting. Every sentence adds value—there is no filler or repetition. The density is appropriate for five parameters and zero schema coverage.

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 5-parameter tool with no schema coverage, no annotations, and no output schema, the description covers purpose, parameter semantics, and usage timing comprehensively. It even includes practical advice like using chat history for `interests`. However, it omits the return value or error behavior, which would be useful for the agent to confirm success, leaving a slight gap in completeness.

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 description fully compensates for the 0% schema description coverage by explaining every parameter: `streams` ⊆ {news, releases, events} with default all, `interests` as standing topic hints, `owner` as {name,email,timezone}, `operator` as {agent,framework}, and `cadence` as 'daily'. This provides semantic meaning beyond the bare schema types (which are generic arrays/objects/null) and includes usage nuance like including chat history in `interests`.

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 states the tool's function: 'Set up (or update) the user's HyperFeed subscription so the digest is scoped and personalized.' This uses a specific verb (set up/update) and resource (HyperFeed subscription), and it distinguishes from siblings like hyperfeed_digest (which likely retrieves the digest) by focusing on the subscription setup.

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?

The description provides direct usage guidance: 'Call once at first run; safe to call again to refine.' It also explains the cadence context ('cadence is daily (you pull each morning)') and clarifies the purpose of parameters like `interests` and `owner`, which helps the agent know when and how to invoke it. It does not explicitly name alternative tools for exclusion, but the 'first run' and 'refine' signals make the appropriate timing clear.

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