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rank_paste

Read-onlyIdempotent

Compute the SigRank yield cascade from pasted token counts. Paste JSON or four numbers to receive yield, SNR, leverage, velocity, 10xDEV score, and operator class tier.

Instructions

Computes the SigRank yield cascade from a paste of token counts. Parses the input, runs the full cascade math locally (no network calls), and returns: Υ Yield (the headline efficiency metric, Υ = Cache Reads × Output / Input²), SNR (signal-to-noise ratio), Leverage ratio (Cr/I = cache reads divided by input), Velocity (O/I = output divided by input), 10xDEV score, operator class tier (Burner / Builder / 10xer), and a deterministic prose "card" summarizing the result in plain English. Accepts two input formats: (1) JSON object {"input":N,"output":N,"cacheCreate":N,"cacheRead":N} or (2) four whitespace-separated numbers in order: input output cacheCreate cacheRead. Returns an error if the input is malformed or has negative values. Use this for a quick one-off ranking without submitting to the board. Do NOT use this to submit your score — use submit_paste instead, which both ranks and publishes. Do NOT use this if you want to rank all four time windows at once — use rank_windows for that. After calling this, use submit_paste to publish the result if you want to appear on the leaderboard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesToken counts to rank. Two formats accepted: (1) JSON object {"input":N,"output":N,"cacheCreate":N,"cacheRead":N} where all values are non-negative integers, or (2) four whitespace-separated numbers in order: input output cacheCreate cacheRead. Get these from `ccusage` output, the Claude Max usage dashboard, tokscale, or any token reader. Example valid input: {"input":1000000,"output":500000,"cacheCreate":50000,"cacheRead":800000}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
snrNoSignal-to-noise ratio
cardNoDeterministic prose summary of the cascade result
classYesOperator class tier
yield_YesΥ Yield — the headline efficiency metric (Cache Reads × Output / Input²)
leverageNoCr/I — cache reads divided by input
tenx_devNo10xDEV score
velocityNoO/I — output divided by input
warningsNoParse or data warnings if any
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that it runs locally with no network calls, returns results without side effects, and handles errors for malformed or negative inputs, providing full transparency.

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

Conciseness4/5

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

The description is somewhat lengthy due to need to explain input formats and output metrics, but it is well-structured and front-loaded with purpose. Could be slightly more concise without losing clarity.

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

Completeness5/5

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

Given the single parameter with full schema coverage, an output schema (not shown but referenced), and moderate complexity, the description covers all necessary context: inputs, outputs, usage guidance, and behavioral traits.

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

Parameters5/5

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

Schema coverage for the single parameter 'text' is 100% with a clear description. The tool description expands on this with two accepted formats and an example, adding significant value beyond the schema.

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?

The description clearly states it computes a SigRank yield cascade from token counts, listing specific output metrics. It explicitly distinguishes from siblings like submit_paste and rank_windows, ensuring the agent knows exactly what this tool does.

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

Usage Guidelines5/5

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

Explicitly provides when to use (quick one-off ranking without submitting) and when not to use (for submitting scores, use submit_paste; for ranking all time windows, use rank_windows). Also advises to use submit_paste afterward to publish.

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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