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get_operator

Read-only

Fetch a specific operator's live SigRank profile by codename: returns yield, leverage, velocity, class tier, rank, and per-window breakdowns.

Instructions

Fetches one operator's live profile from the SigRank board by their codename. Reads the operator's current submission data from signalaf.com and returns their detailed metrics: yield (Υ), leverage ratio (Cr/I), velocity (O/I), class tier (Burner / Builder / 10xer), rank position (integer, 1-based), and per-window breakdowns for each time range (7d, 30d, 90d, all-time) with the four canonical pillars (input, output, cacheCreate, cacheRead) per window. Returns an error if the codename is not found on the board. Use this to look up any operator who has submitted to the board — codenames are public and visible on the leaderboard. Do NOT use this to browse all operators — use get_leaderboard for that. After calling this, you can use simulate_change to model what would happen if the operator adjusted their token mix.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codenameYesThe operator's public codename as shown on the SigRank leaderboard. Case-insensitive — "Ghost Falcon" and "ghost falcon" are equivalent. Must match a codename that exists on the board; returns an error if not found. To discover valid codenames, call get_leaderboard first.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rankNo1-based rank position
classNo
yield_NoΥ Yield metric
windowsNoPer-window breakdowns (7d, 30d, 90d, all-time)
codenameNoOperator display name
leverageNoCr/I ratio
velocityNoO/I ratio
Behavior4/5

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

Annotations already indicate readOnlyHint=true, but description adds details: returns detailed metrics, error if codename not found, and source (signalaf.com). No contradictions.

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?

Multiple sentences but each adds value: purpose, output details, error handling, usage guidance, exclusion of alternatives, and follow-up suggestion. Efficient and well-structured.

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 tool's complexity and available output schema, description covers purpose, input, output, errors, usage scope, and next steps. No gaps.

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 is 100% already, and description adds crucial meaning: case-insensitivity, requirement to exist, and guidance to call get_leaderboard first to discover valid codenames.

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?

Clearly states it fetches one operator's live profile by codename, and explicitly distinguishes from sibling get_leaderboard (browse all operators). The verb 'fetches' and resource 'operator's live profile' are specific.

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 says 'Use this to look up any operator...' and 'Do NOT use this to browse all operators — use get_leaderboard for that'. Also suggests follow-up tool simulate_change, providing a complete usage context.

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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