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lmorchard

Oblique Strategies MCP Server

by lmorchard

get_strategy

Retrieve a random creative prompt from Brian Eno's Oblique Strategies deck to overcome creative blocks and stimulate lateral thinking.

Instructions

Get a random oblique strategy from the specified edition.

Args: edition: The edition to use (edition-1, edition-2, edition-3, edition-4, condensed, programmers, do-it). Defaults to edition-2.

Returns: A dictionary containing the strategy text and edition information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
editionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The actual implementation of the strategy retrieval logic.
    def get_random_strategy(
        self, edition: Optional[str] = None
    ) -> Dict[str, Union[str, int]]:
        """Get a random strategy from the specified edition."""
        if edition is None:
            edition = self.DEFAULT_EDITION
    
        try:
            strategies = self.load_strategies(edition)
            if not strategies:
                return {
                    "error": f"No strategies found in edition: {edition}",
                    "edition": edition,
                }
    
            strategy = random.choice(strategies)
            return {
                "strategy": strategy,
                "edition": edition,
                "total_in_edition": len(strategies),
            }
        except FileNotFoundError as e:
            return {"error": str(e), "edition": edition}
        except Exception as e:
            return {"error": f"An error occurred: {str(e)}", "edition": edition}
  • The registration of the 'get_strategy' tool using the FastMCP decorator, which delegates to the StrategiesManager.
    @mcp.tool()
    def get_strategy(edition: Optional[str] = None) -> Dict[str, Union[str, int]]:
        """
        Get a random oblique strategy from the specified edition.
    
        Args:
            edition: The edition to use (edition-1, edition-2, edition-3, edition-4,
                    condensed, programmers, do-it). Defaults to edition-2.
    
        Returns:
            A dictionary containing the strategy text and edition information.
        """
        return manager.get_random_strategy(edition)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns a random strategy, which is useful, but doesn't describe other behavioral traits such as whether it's idempotent, has rate limits, requires authentication, or what happens on errors. For a tool with zero annotation coverage, this leaves significant gaps.

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?

The description is appropriately sized and front-loaded, with the core purpose in the first sentence and parameter details in a structured format. Every sentence earns its place by providing essential information without redundancy or fluff.

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?

Given the tool's low complexity (1 parameter) and the presence of an output schema (which handles return values), the description is mostly complete. It covers purpose, parameter details, and return format at a high level. However, it could be more complete by addressing behavioral aspects like randomness or error handling, given the lack of annotations.

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

Parameters4/5

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

The schema description coverage is 0%, so the description must compensate. It provides the parameter 'edition' with a clear list of allowed values (edition-1 through edition-4, condensed, programmers, do-it) and specifies the default as edition-2, adding meaningful semantics beyond the bare schema. This adequately covers the single parameter.

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 clearly states the specific action ('Get a random oblique strategy') and resource ('from the specified edition'), distinguishing it from sibling tools like list_editions and search_strategies. It precisely defines what the tool does without being vague or tautological.

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?

The description provides clear context for when to use this tool (to get a random strategy from a specific edition), but it doesn't explicitly state when not to use it or mention alternatives like search_strategies for non-random searches. The context is clear but lacks explicit exclusions or comparisons.

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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