my quant doesn’t speak english — editorial discovery

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

Annotations already carry the heavy lifting with readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false. The description adds genuine value beyond these by disclosing that no user state is read or changed and that the heartbeat is non-sensitive, which reinforces the privacy/safety profile. This is useful, non-redundant behavioral context.

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?

A single, tightly packed sentence with zero filler. The safest and most distinctive trait ('non-sensitive', no state access) is front-loaded, and every clause 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 parameterless, annotation-rich health-check tool, the description is complete: an agent knows it is a safe, state-independent compatibility probe. No output schema exists, but the return value of a heartbeat check is self-evident, so nothing critical 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?

With zero parameters and 100% schema coverage, there is nothing for the description to document. This is the baseline-4 case for a parameterless tool, and no additional param meaning is needed.

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 verb 'Return' plus the resource 'API and MCP compatibility heartbeat' gives a specific, actionable purpose, and 'without reading or changing user state' scopes it further. It is distinguishable from the sibling list_capabilities by intent, though it doesn't name the sibling. The term 'heartbeat' is slightly abstract but well qualified by 'non-sensitive' and 'compatibility.'

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 conveys context — a safe, non-sensitive health check — that implies when to call it, but it provides no explicit when-to-use guidance, exclusions, or mention of the sibling list_capabilities as an alternative. The usage context is inferred rather than stated.

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

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

Annotations already convey readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description is consistent with those annotations, adding that the tool enumerates boundaries across six specific domains. It doesn't reveal the response structure or behavior beyond the listing, but for a pure read-only listing tool, this is adequate.

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?

A single, front-loaded sentence with the verb 'List' leading the description. The comma-separated enumeration of domains is compact, though the sentence is slightly dense to parse. Every word 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 zero-parameter, read-only discovery tool, the description covers what the tool lists and its scope. However, the term 'boundaries' is never defined, and with no output schema provided, an agent must infer what a boundary looks like until runtime. It is adequate but leaves a notable gap.

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 tool has zero parameters, and schema coverage is 100% (vacuously). Per the rubric, 0 params earns a baseline of 4, and there is nothing for the description to compensate for regarding parameter meaning. The description's silence on parameters is appropriate.

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 and resource: 'List the current briefing, evidence-network, app-feed, API, MCP, and interpretation boundaries.' This clearly communicates a discovery/listing tool for product capabilities. However, 'boundaries' is slightly ambiguous without domain context, preventing a higher score.

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?

Usage is implied by the name and description — an agent would call this to understand the editorial product's scope before acting. However, there's no explicit guidance on when to use this over the sibling tool `get_health`, nor any exclusions mentioned. The context is absent rather than wrong.

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