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SigRank — AI Operator Benchmarking

by com.signalaf

Get Leaderboard — Public Operator Rankings

get_leaderboard
Read-onlyIdempotent

Read the current public SigRank operator leaderboard. Returns ranked operators with Yield, Leverage, class tier, and display name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of operators to return (1–100, default 25).
windowNoTime window for the leaderboard: 7d, 30d, 90d, or all_time.30d

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNoThe time window used for the query.
entriesNo
total_operatorsNoNumber of operators returned.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior; the description aligns with these and adds useful context by specifying the leaderboard is 'public' and 'current'. It also states the return content, which is helpful 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.

Conciseness5/5

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

Two short sentences with no filler. The action and resource are front-loaded, and the returned fields are concise. Every sentence contributes useful information.

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?

For a simple read-only list tool with an output schema, fully documented parameters, and clear annotations, the description is complete enough for an agent to select and invoke the tool correctly. No critical information is missing.

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

Parameters3/5

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

Both parameters (limit, window) are fully described in the input schema with defaults, ranges, enums, and descriptions. The description adds no additional parameter-level semantics, but the schema already carries the full burden of documentation.

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 uses a specific verb ('Read'), names the exact resource ('current public SigRank operator leaderboard'), and enumerates the returned fields (Yield, Leverage, class tier, display name). This clearly distinguishes it from sibling tools like get_operator.

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?

The description clearly communicates when to use this tool: when you need the public operator leaderboard. It does not explicitly discuss alternatives or exclusions, but the context is sufficiently clear and self-contained.

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

All SigRank — AI Operator Benchmarking toolsInspect
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TDQS

B3.4/5.0
Disambiguation2/5

Several tools have significantly overlapping purposes: benchmark_me and compare_to_field both compare a user's cascade to the field, operator_signature and who_operates_like_me both find comparable operators, and rank_paste/rank_windows overlap as metric calculators. Descriptions clarify the output format, but an agent would frequently struggle to pick the right tool.

Naming Consistency3/5

All names are lowercase snake_case, which is readable, but the pattern is mixed: get_leaderboard and simulate_change are verb-first, field_anomaly and operator_gap are noun-first, and rank_if, rank_paste, benchmark_me, and who_operates_like_me break the convention entirely. There is a loose semantic system, but no strong predictable verb_noun pattern.

Tool Count3/5

16 tools sits right at the heavy borderline, and the count feels inflated by overlapping tools that could be consolidated. The domain is broad enough to justify more than a handful of tools, but the duplication makes the set feel heavier than its actual functional surface.

Completeness4/5

The tool set covers the core benchmarking workflow well: reading leaderboard/operator data, computing metrics, comparing to the field, diagnosing weaknesses, simulating changes, and suggesting improvements. There are minor gaps, such as no way to retrieve a user's raw token pillars from a codename for simulation tools that require four pillars, but these are workable.

Resources