ctx_health

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

With no annotations, the description carries full behavioral burden, and it does disclose meaningful traits: the exact components probed, a 30-second server-side in-memory cache (i.e., results may be stale by up to 30s), and the returned shape with the ok|degraded|fail status domain. It omits any note about auth/permission requirements or whether it is strictly read-only, which would matter for a prod-facing probe.

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 tight sentences, front-loaded with the action and followed by scope, caching behavior, and return shape. The trailing 'from MCP clients' is slightly redundant, but no sentence is wasted.

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 diagnostic with no output schema, the description supplies everything an agent needs: what is checked, the caching/staleness caveat, the return keys, and the status enumeration. Nothing essential 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?

The tool takes zero parameters and the schema is empty with 100% coverage, so there is nothing for the description to clarify. Baseline 4 applies; no parameter guidance is needed or missing.

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 ('Run the deep health probe') and scopes it as deep vs. shallow by enumerating exactly what is probed (DB, Elasticsearch, embedding, LLM, schedulers). It does not explicitly distinguish itself from the sibling ctx_stats, which an agent could plausibly confuse with a health probe.

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?

Gives clear context for use ('ad-hoc prod health checks from MCP clients'), which tells the agent this is an on-demand diagnostic rather than a routine data call. It offers no exclusions or named alternative (e.g., when to prefer ctx_stats instead), so it stops short of a 5.

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