my quant — finite market briefing

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

Beyond the annotations for read-only and idempotent, the description adds an explicit guarantee that it does not even read or change on-device state and returns only non-sensitive information. This is more restrictive than the annotations alone, so it meaningfully clarifies behavior.

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?

One sentence, front-loaded with the operation and resource, with no filler. It conveys the read-only guarantee and sensitivity level efficiently.

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?

The tool is parameterless, has no output schema, and the description covers what to expect in terms of scope and sensitivity. A specific detail about the exact response shape might be helpful, but it is a simple health probe, so what is provided is adequate.

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 the schema already covers the empty inputs. The description adds no parameter details but does not need to; the behavioral focus is appropriate for a parameterless health check.

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 states a specific verb ('Return') and resource ('non-sensitive API and MCP compatibility heartbeat'), and the title reinforces the public-surface check. It is clearly a health probe, not a capabilities listing, so it distinguishes itself from the sibling list_capabilities.

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 makes it clear this is for a low-risk, read-only health/compatibility check. It gives clear context for when to call it, though it does not explicitly name alternatives or say when not to use it.

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 indicate read-only, non-destructive, idempotent behavior, so the description does not need to repeat that. However, it adds no additional behavioral context such as authentication requirements, rate limits, or side effects. Since annotations cover the core traits, a neutral score is appropriate.

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 a single sentence and includes the core action upfront. It lists multiple items, which makes it slightly long-winded, but it remains focused and does not include irrelevant details. The structure is acceptable and reasonably concise.

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, and the description does not mention what the tool returns. It lists what is being listed, but not the format, structure, or content of the response. An agent would need additional context to know whether to expect a list, an object, or other data. This is 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?

There are no parameters in the schema, so schema coverage is 100%. No additional parameter semantics are needed. The description does not add any param-related detail, but the baseline for high coverage is 3.

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 action ('List') and specifies the exact items being listed (briefing, feed validation, offline reading, topic controls, API, MCP, product boundaries). It is distinct from the sibling tool get_health, which presumably checks health status, so an agent can easily differentiate purposes.

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?

No explicit guidance is given on when to use this tool versus alternatives. There is no mention of scenarios that would favor listing capabilities over checking health. The description only states what the tool does, not when to invoke it.

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