simulate_change

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

Annotations declare readOnlyHint=true and idempotentHint=true. Description adds context: 'no network, no submission, pure local math,' and details the exact return values (Υ Yield delta, class change, per-metric diffs). This enriches the behavioral profile beyond the annotations.

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?

Description is front-loaded with the key value proposition ('first PRESCRIPTIVE SigRank tool'). It's moderately long but each sentence adds essential information. Could be slightly more concise, but no fluff.

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?

Given the tool's moderate complexity (2 parameters, nested objects, output schema exists), the description covers purpose, usage scenario, parameter formats with examples, behavioral nature (local math), and return values. No gaps left.

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 description adds meaningful context: explains the 'text' parameter accepts JSON or 4 numbers (same format as rank_paste) and the 'changes' parameter accepts absolute numbers or relative deltas with '+/-' prefix, including an example. This compensates for the schema's generic descriptions.

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 starts with a clear, specific verb-resource pair: 'what if I changed my token mix?' It explains it simulates changes to token pillars and returns yield delta, class change, and per-metric diffs. This distinguishes it from siblings like rank_paste (which only calcs current) and diagnose_cascade (which may analyze issues).

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?

Explicitly states when to use: 'show me the payoff before I do the work' and 'use it to answer would increasing... before you change your workflow.' Mentions it's local math with no network. However, it does not explicitly list when not to use it or directly compare to other tools like diagnose_cascade.

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