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lmorchard

Oblique Strategies MCP Server

by lmorchard

search_strategies

Find creative problem-solving strategies by searching keywords across Brian Eno's Oblique Strategies card deck to overcome creative blocks.

Instructions

Search for strategies containing the specified keywords.

Args: query: Keywords to search for (case-insensitive). edition: Optional edition to limit search to. If not specified, searches all editions.

Returns: A dictionary containing matching strategies and their editions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
editionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The actual business logic for the search_strategies tool, which filters strategies by query and edition.
    def search_strategies(
        self, query: str, edition: Optional[str] = None
    ) -> Dict[str, Any]:
        """Search for strategies containing the specified keywords."""
        query_lower = query.lower()
        results = []
    
        # Determine which editions to search
        editions_to_search = (
            [edition] if edition and edition in self.EDITIONS else self.EDITIONS.keys()
        )
    
        for ed in editions_to_search:
            try:
                strategies = self.load_strategies(ed)
                for strategy in strategies:
                    if query_lower in strategy.lower():
                        results.append({"strategy": strategy, "edition": ed})
            except (FileNotFoundError, Exception):
                # Skip editions that can't be loaded
                continue
    
        return {
            "query": query,
  • MCP tool registration and entry point for search_strategies.
    @mcp.tool()
    def search_strategies(query: str, edition: Optional[str] = None) -> Dict[str, Any]:
        """
        Search for strategies containing the specified keywords.
    
        Args:
            query: Keywords to search for (case-insensitive).
            edition: Optional edition to limit search to. If not specified,
                    searches all editions.
    
        Returns:
            A dictionary containing matching strategies and their editions.
        """
        return manager.search_strategies(query, edition)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions that the search is 'case-insensitive', which is useful behavioral context. However, it doesn't disclose other important traits like whether this is a read-only operation, potential rate limits, authentication needs, or pagination behavior for a search tool.

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?

The description is appropriately sized and front-loaded with the core purpose in the first sentence. The 'Args' and 'Returns' sections are structured clearly, though the 'Returns' section could be slightly more detailed. Overall, it's efficient with minimal waste.

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 moderate complexity (2 parameters, search functionality), the description is fairly complete. It explains parameters and return values, and an output schema exists, so detailed return explanations aren't needed. However, without annotations, it could benefit from more behavioral context like safety or performance notes.

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 description adds significant meaning beyond the input schema, which has 0% description coverage. The 'Args' section explains that 'query' is for 'keywords to search for (case-insensitive)' and 'edition' is 'optional' to 'limit search to', clarifying semantics that aren't in the schema. With 2 parameters and good coverage in the description, this compensates well.

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 clearly states the tool's purpose: 'Search for strategies containing the specified keywords.' It specifies the verb ('search') and resource ('strategies'), but doesn't explicitly differentiate from sibling tools like 'get_strategy' or 'list_editions', which would require a 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?

The description implies usage through the 'Args' section, which explains when to use the optional 'edition' parameter, but it doesn't provide explicit guidance on when to choose this tool over alternatives like 'get_strategy' or 'list_editions'. No exclusions or prerequisites are mentioned.

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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