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simulate_change

Simulate changes to your token pillars and see the exact yield delta, class change, and per-metric diffs before modifying your workflow.

Instructions

The first PRESCRIPTIVE SigRank tool — 'what if I changed my token mix?' Takes your current 4 pillars (input/output/cacheCreate/cacheRead) and one or more proposed changes, runs the canonical cascade on BOTH the current and simulated values, and returns the exact Υ Yield delta, class change, and per-metric diffs. This is the 'show me the payoff before I do the work' primitive: no network, no submission, pure local math. Use it to answer 'would increasing my cache-read by 50k tokens actually move my class?' before you change your workflow. Accepts the current pillars as JSON or 4 numbers (same as rank_paste) plus a changes object with any of the 4 pillar names mapped to new absolute values OR relative deltas (e.g. {cacheRead: '+50000'} or {input: 800000}).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesCurrent token pillars — ccusage JSON or "input output cacheCreate cacheRead" (same format as rank_paste).
changesYesProposed changes to apply. Keys: input, output, cacheCreate, cacheRead. Values are either absolute numbers (replace) or strings starting with +/- for relative deltas (add/subtract). Omitted pillars are unchanged.
Behavior4/5

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

With no annotations, the description fully carries the behavioral explanation. It states the tool is local math (non-destructive, no network), explains input formats (current pillars and changes with relative/absolute deltas), and specifies output elements (Yield delta, class change, per-metric diffs). This provides sufficient insight into tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured paragraph of ~100 words. It front-loads the core concept, then explains input/output and usage. Every sentence serves a purpose without redundancy or irrelevant detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description adequately explains return values (exact Yield delta, class change, per-metric diffs). It covers input formats and change semantics. Possible improvements include error behavior or restrictions, but given the tool's simplicity, the description is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the overall structure ('same as rank_paste' and 'changes object with relative deltas') and providing an example format, which improves clarity beyond the schema's parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly identifies the tool as a 'prescriptive' simulation primitive for exploring token mix changes. It explicitly distinguishes from sibling submission tools by stating 'no network, no submission, pure local math' and uses the phrase 'show me the payoff before I do the work.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description provides explicit use case ('would increasing my cache-read by 50k tokens actually move my class?') and contrasts with execution tools. However, it does not explicitly state when not to use the tool or list alternatives, though the sibling list and context make the distinction clear.

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

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