fcs_withdrawal

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so safety is covered. The description goes meaningfully beyond that by disclosing evaluation semantics that are not in the schema: unset outcomes never collapse to a negative, and a favourable human-grain outcome does not corroborate M2 because the methodological bias favours the field. That asymmetry is genuine behavioral context an agent could not derive from structured fields.

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 dense sentences that front-load the core action and then add the decisive null-handling rule. Little waste, though the second half leans on undefined jargon (M2, human grain) that compresses at the cost of comprehension.

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, no annotations on parameter meaning, and 0% schema coverage on 8 flags, the description should explain what the inputs represent and roughly what comes back. It supplies the undetermined-collapse rule but leaves every parameter and the entire result shape unexplained, which is a serious gap for a tool whose whole surface is these eight flags.

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?

Schema description coverage is 0% across 8 parameters, so the description must carry the burden, and it largely does not. It explains the null/unset convention in general terms but never maps any of the concrete flags (bridgeCovariation, experimentRankedByM1, ephapticPropagationUnderBlockade, etc.) to the theses they govern. An agent still cannot tell what a given boolean actually asserts.

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 a specific verb (evaluate) and resource (the protective belt / withdrawal conditions), and states what the evaluation yields: which theses are withdrawn, stand, undetermined, and what survives each withdrawal. That is more than a restatement of the name. It stops short of distinguishing itself from the many other fcs_* siblings (fcs_report, fcs_conformance, fcs_stratify), so an agent cannot route between them on the strength of this text alone.

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 when-to-use directive, no prerequisites, and no mention of any alternative tool. The agent must infer that this is called after experimental outcomes are known, but nothing states the trigger condition or which sibling to prefer instead. Usage is only implicit for a domain-jargon task.

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