dm_status

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

With no annotations, the description carries the full behavioral burden. It discloses the diagnostic content and implies it is a safe probe, but never states that it is read-only or side-effect free, nor what the response shape looks like. The guidance 'do not restart DM because of this' adds useful operational 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?

Two sentences: the first front-loads the enumerated self-check contents, the second front-loads the usage trigger and the misdiagnosis warning. No filler.

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?

With no output schema, the enumeration of what gets reported (backend, versions, manual path) is the right compensation and is present. Only the read-only/no-side-effect guarantee is missing, a minor gap for a diagnostic probe.

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, so there is nothing to disambiguate; the baseline for a parameterless tool applies. The description correctly does not invent parameter guidance.

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 names the tool as a link self-check and enumerates exactly what it probes: bridge backend (digitalmicrograph/mock), DM version, host Python and numpy versions, and the offline manual path. It does not explicitly contrast with the dm_* data siblings, but the diagnostic intent is unmistakable against tools like dm_metadata or dm_stats.

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?

It gives a clear trigger ('when DM connection or native operation errors') and an explicit exclusion routing to a different check ('local preview/report dependency errors should check DM_ANALYSIS_PYTHON, don't restart DM'). This is the when/when-not/alternative pattern in full.

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