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Collision Engine

collision_engine
Read-only

Score every note pair to surface unexpected, useful combinations, then turn the top collisions into concrete ideas. Set a pair cap to control cost.

Instructions

Find surprising, useful combinations in a pile of notes by scoring every pair with Jev. Give either a folder/file path or a list of notes. Returns the top collisions; develop each into a concrete idea. maxPairs caps cost (2,000 pairs is typically well under $0.05).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNo
lensNoOptional focus, e.g. "startup ideas", "short stories"
pathNoFolder of .md/.txt notes, or one file with notes separated by blank lines
notesNoNotes as plain strings (alternative to path)
maxPairsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint, openWorldHint), and the description adds genuinely new context: it discloses the return shape ('returns the top collisions') and a concrete cost characteristic for maxPairs (2,000 pairs under $0.05). It does not discuss defaults or failure modes, so not a 5.

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?

Three tight, front-loaded sentences: purpose first, then input forms, then return/cost. Every sentence contributes, with only mild redundancy in 'develop each into a concrete idea'.

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?

With no output schema and zero required parameters, the description shoulders return-value explanation reasonably ('returns the top collisions') and covers cost via maxPairs. It remains silent on the 'top' default and what 'lens' does to output, so a small completeness gap remains.

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?

Schema coverage is 60%, so the schema already documents path/notes/items well. The description adds real meaning for maxPairs by tying it to cost, and clarifies path vs notes as alternatives, but it omits any mention of 'top' or 'lens', leaving those parameters to the schema alone.

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

Purpose4/5

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

States a specific verb+resource ('find ... combinations in a pile of notes') plus the mechanism ('scoring every pair with Jev'), which is distinctive enough to separate it from generic search tools. It does not explicitly name or contrast any sibling (jev_ask, semantic_bisect, etc.), so 4 rather than 5.

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

Usage Guidelines3/5

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

It tells the agent the accepted inputs ('either a folder/file path or a list of notes') and a follow-up step ('develop each into a concrete idea'), which implies intended usage. However, there is no explicit when-to-use vs when-not, and no routing to alternative sibling tools for related tasks.

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