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Premiss

Save a strategy

create_strategy
Idempotent

Save a new private strategy using custom Python files and complete rules text, on any Premiss-supported market and timeframe. Accepts either files (strategy.py plus helper modules) and rules, or a convenience template. Uses the same package format as the app. Returns code and revision; saving does not run a backtest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
filesNo
rulesNo
symbolYes
intervalYes
templateNo
request_keyYesIdempotency UUID identifying one requested write and its unchanged arguments.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
nameYes
filesNo
rulesYes
venueNo
symbolYes
app_urlYes
versionYes
intervalYes
revisionYes
templateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare non-read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real context beyond that: the save is private, it returns code and revision, and notably 'saving does not run a backtest', which prevents the agent from expecting backtest output.

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?

Three tight sentences, front-loaded with the core action and scope, then the input modes, then the side-effect clarification. No filler and no repetition of schema or annotation content.

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?

Covers the complex parts an agent needs: dual input paths, the package-format compatibility, and the fact that no backtest is triggered. Output schema exists so return values needn't be detailed, though the description adds that anyway. Missing only minor points such as whether files and template are mutually exclusive or whether name must be unique.

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 only 14%, so the description has to carry the load. It clarifies the files-vs-template alternative and the shape of files ('strategy.py plus helper modules'), but leaves symbol, interval, name, and the four required rules fields (watches/buys/sells/safety) unexplained.

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?

States a specific verb and resource ('Save a new private strategy') plus scope ('any Premiss-supported market and timeframe'), and the word 'new' implicitly separates it from the sibling update_strategy. An agent can pick between the two without opening either schema.

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?

Gives clear routing between the two input modes ('Accepts either files ... and rules, or a convenience template'), which is the main usage decision for this tool. It stops short of an explicit when-not or a direct comparison against update_strategy/start_backtest.

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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