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Model Ruler — AI Cost Calculators

RAG Pipeline Cost Calculator

rag-pipeline-cost-calculator
Read-onlyIdempotent

Use when a user needs end-to-end RAG cost estimation (embedding + vector store + generation). Returns monthly cost with breakdown and dominant-component identification.

Input Schema

NameRequiredDescriptionDefault
vector_storeNoVector store
answer_tokensNoAvg answer tokens (default 400)
corpus_tokensYesIndexed corpus size in tokens
generator_modelNoGenerator model (default claude-sonnet-4-6)
queries_per_dayYesUser query volume per day
question_tokensNoAvg question tokens (default 100)
chunks_retrievedNoChunks per query (default 5)
chunk_size_tokensNoAvg chunk size (default 512)
embedding_providerNoEmbedding model
generator_providerNoGenerator LLM provider (default anthropic)
reindex_fraction_per_monthNoFraction of corpus re-embedded per month (default 0.1)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuine value beyond that by disclosing the return shape (monthly cost with breakdown and dominant-component identification), which matters since no output schema exists.

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 sentences, both load-bearing: the first gives the usage trigger, the second gives the return semantics. Front-loaded and free of filler.

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?

For an 11-parameter, no-output-schema calculator, the description covers the trigger and the returned artifacts (total cost, breakdown, dominant component), which is the essential missing piece. It omits currency/units assumption and any note on how pricing tables are sourced or how current they are, leaving minor gaps.

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 description coverage is 100% across 11 parameters, so the schema already documents defaults, enums and units for each field. The description's "embedding + vector store + generation" phrasing loosely frames the three modeling dimensions but adds no syntax, default or constraint detail beyond the schema. Baseline 3 applies.

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?

The description states a specific verb (cost estimation) and resource (end-to-end RAG pipeline, spelled out as embedding + vector store + generation), which cleanly separates it from siblings like provider-cost-calculator or token-counter by scope. It does not, however, name any sibling it should not be confused with, so it stops short of full differentiation.

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?

"Use when a user needs end-to-end RAG cost estimation" is an explicit trigger condition, which is better than implied usage. There is no when-not guidance or pointer to alternative calculators (e.g. self-host-breakeven-calculator) for adjacent questions, so exclusions are missing.

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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