SigRank — AI Operator Benchmarking

Who Operates Like Me — Nearest Neighbor Finder

who_operates_like_me

Read-onlyIdempotent

Finds operators whose operating signature most resembles yours. Takes 4 pillars or a codename, computes your signature, then searches the live leaderboard for the nearest neighbors by signature distance. Returns: nearest operators, similarity %, where they outperform you, where you outperform them, and what separates you from the better operator. Makes the leaderboard feel like a network, not a list.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`input`	No
`limit`	No	Number of nearest neighbors to return (default 5)
`output`	No
`window`	No		30d
`context`	Yes	Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
`codename`	No	Operator codename (alternative to pillars)
`cache_read`	No
`cache_write`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 3, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / context

Added value: +{
+  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
+  "type": "string"
+}

addedInput schema / required
```
Added value: +[
+  "context"
+]
```

First observedSep 1, 2026

TDQS

A3.9/5.0

Behavior4/5

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

The annotations already declare the tool read-only and idempotent, and the description adds behavioral detail beyond that: it computes a signature, queries the live leaderboard, and produces a comparative breakdown including outperformance directions. No contradictory claims are present.

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 main functional flow is conveyed in two tight sentences and the return payload is listed compactly. The closing sentence ('Makes the leaderboard feel like a network, not a list') is stylistically nice but not functionally necessary, preventing a perfect score.

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

Completeness3/5

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

The return fields are enumerated, which compensates for the missing output schema, and the processing flow is clear. But with eight parameters, no example, and an ambiguous '4 pillars' reference, the description is not complete enough for an agent to confidently construct a non-default call.

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

Parameters2/5

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

Schema description coverage is only 38%, so the description must carry much of the parameter-meaning burden. It says 'Takes 4 pillars or a codename' but never maps the four pillars to the actual schema fields, leaving the numeric parameters ambiguous. Limit, window, and context are already explained in the schema, so the description adds little parameter-level value.

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 opens with a specific verb and resource ('Finds operators whose operating signature most resembles yours') and adds the discriminator 'nearest neighbors by signature distance.' This separates it from siblings like get_leaderboard or operator_signature, making the tool's unique purpose immediately clear.

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?

It gives a clear usage context: pass four pillars or a codename, and it will compute a signature and search the live leaderboard for similar operators. However, it does not name alternative tools or explicitly state when not to use it, so it stops short of full routing guidance.

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 tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Who Operates Like Me — Nearest Neighbor Finder

Input Schema

Schema Changelog

TDQS

Glama MCP Gateway

Resources