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Premiss

Read a saved strategy

get_strategy
Read-onlyIdempotent

Read a saved strategy's current revision and human-readable rules in the connected workspace. Returns the complete Python package for review or editing. Code and comments are user-authored content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
strategy_idYes

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

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing that the return is a full Python package and flagging code/comments as user-authored content, which is a meaningful caution for an agent consuming untrusted text. It stops short of stating auth requirements or behavior when the strategy_id does not exist.

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 sentences with the core action front-loaded and no filler. The 'Code and comments are user-authored content' note earns its place as a safety-relevant caveat.

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?

An output schema exists, so return-value documentation is not strictly required, yet the description still summarizes the payload shape usefully. Combined with annotations covering the safety profile, an agent has nearly everything needed, with only parameter sourcing left implicit.

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 0% and the single strategy_id parameter has only type and length constraints, so the description must carry semantic weight. It implies the identifier selects 'a saved strategy in the connected workspace' but adds no format, provenance, or how-to-obtain guidance beyond that.

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 and resource ('Read a saved strategy's current revision and human-readable rules') and clarifies the payload is a complete Python package. It is clearly distinct from create_strategy and update_strategy by verb, though it never explicitly names those siblings.

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?

Usage is implied by 'for review or editing,' which hints at a read-before-update workflow, but there is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives such as get_strategy_guide or update_strategy.

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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