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

Annotations already declare readOnly/destructive/idempotent, but the description adds real value beyond them: the pricing model ($0.01/call, first 25 free, failed calls free) and the explicit explanation that repeats are charged, which reconciles the surprising idempotentHint=false. It does not say what happens on malformed JSON (error vs. repair), the one remaining behavioral gap.

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?

Front-loaded with purpose, then usage, then example, then commercial terms — logical order with no filler. The pricing sentence is longer than the rest but carries information an agent cannot get elsewhere.

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 description correctly states the return value (formatted text) and covers cost and side-effect profile. Only the invalid-input failure mode is left unspecified, which is a modest gap for a pure-transformation tool.

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 coverage is 100% and the schema already documents text, indent (2 default, 4 or tab) and sortKeys. The description repeats the same indent options and shows one example object, adding only marginal meaning beyond the structured fields, so baseline 3 applies.

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 (format JSON) plus the two axes of behavior (indentation, key sorting) and names the return value. The example input makes it clearly distinguishable from siblings like json_minify, json_validate, json_repair and json_schema.

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?

"Use to make machine JSON readable or to normalise it for diffs" gives concrete usage contexts, which is stronger than implied usage. It never names an alternative tool or exclusion (e.g. use json_minify to compact, json_validate to check), so it stops short of explicit when-not guidance.

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