cluster_load

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

Annotations only establish that this is a safe, open read; the description goes much further by warning that 'planned' nodes look idle in plain sinfo %A/%F but are not available to new jobs except via short backfill. That caveat preempts a concrete misreading of the output, and the fair-share/4× heuristics add decision-relevant context the schema cannot carry.

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?

It is front-loaded with 'Nodes per partition' and every clause carries new information, with nothing redundant. It loses a point for density: an 80-word sentence with a nested parenthetical (backfill exception) is hard to parse on a first read when it could have been split into shorter clauses.

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?

Zero parameters, no output schema, and read-only, so the only thing an agent needs is what comes back and how to interpret it — the description enumerates every bucket (allocated, idle, planned, other, total, states, jobs, fair-share) and explains the non-obvious one. Nothing material is missing for correct invocation.

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 no parameters, so there is no parameter semantics to document; a baseline of 4 applies. The description's detail goes into output fields instead, which is the right allocation of space for a zero-argument call.

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 enumerates exactly what the tool reports: per-partition node counts by allocation category, per-state node counts, job counts, and the caller's fair-share/priority factors. That is a precise, verifiable resource breakdown rather than a tautology. It never names a sibling, though, so an agent must infer on its own why this differs from access_status or list_jobs.

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?

There is no explicit 'use this when...' or exclusion statement; the fit is only implied by phrases like 'job next in line' and 'low fair-share means long waits,' which suggest the tool serves pre-submission timing decisions. The closing note that idle GPU nodes can take CPU work at 4× hints at an actionable interpretation, but the agent is left to derive that this is the tool to reach for before submitting rather than, say, check_job.

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