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lmwharton/sieve-mcp

sieve_memo

Retrieve existing investment memos or generate new ones for deals. Choose between internal (IC-facing) or external (founder-facing) format. Requires a completed screen.

Instructions

Get or generate an investment memo for a deal.

If generate=false (default), retrieves the existing memo. If generate=true, creates a new memo (~15-30 seconds). Requires a completed screen.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deal_idYesThe deal ID (from sieve_deals or sieve_screen).
generateNoSet to true to generate a new memo.
memo_typeNo'internal' (IC-facing, full risks) or 'external' (founder-facing). Default: internal.internal

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The sieve_memo tool is registered as a FastMCP tool with @mcp.tool decorator, defining its annotations, docstring, and handler function signature taking deal_id, generate, and memo_type parameters.
    @mcp.tool(
        annotations={
            "readOnlyHint": False,
            "destructiveHint": False,
            "openWorldHint": True,
        }
    )
    async def sieve_memo(deal_id: str, generate: bool = False, memo_type: str = "internal") -> dict:
        """Get or generate an investment memo for a deal.
    
        If generate=false (default), retrieves the existing memo.
        If generate=true, creates a new memo (~15-30 seconds).
        Requires a completed screen.
    
        Args:
            deal_id: The deal ID (from sieve_deals or sieve_screen).
            generate: Set to true to generate a new memo.
            memo_type: 'internal' (IC-facing, full risks) or 'external' (founder-facing). Default: internal.
        """
        return await client.memo(deal_id=deal_id, generate=generate, memo_type=memo_type)
  • The sieve_memo handler function delegates to client.memo(), passing deal_id, generate, and memo_type arguments.
    async def sieve_memo(deal_id: str, generate: bool = False, memo_type: str = "internal") -> dict:
        """Get or generate an investment memo for a deal.
    
        If generate=false (default), retrieves the existing memo.
        If generate=true, creates a new memo (~15-30 seconds).
        Requires a completed screen.
    
        Args:
            deal_id: The deal ID (from sieve_deals or sieve_screen).
            generate: Set to true to generate a new memo.
            memo_type: 'internal' (IC-facing, full risks) or 'external' (founder-facing). Default: internal.
        """
        return await client.memo(deal_id=deal_id, generate=generate, memo_type=memo_type)
  • The client.memo() helper function makes the HTTP API call: POST /deals/{deal_id}/memo (with memo_type body) if generate=True, otherwise GET /deals/{deal_id}/memo to retrieve the existing memo.
    async def memo(deal_id: str, generate: bool = False, memo_type: str = "internal") -> dict[str, Any]:
        """Get or generate investment memo."""
        if generate:
            return await _request("POST", f"/deals/{deal_id}/memo", json_body={"type": memo_type}, timeout=60.0)
        return await _request("GET", f"/deals/{deal_id}/memo")
Behavior4/5

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

Annotations indicate readOnlyHint=false, so mutation is expected. Description adds time estimate (~15-30 seconds) for generation and precondition (completed screen), which are valuable beyond annotations. No contradictions.

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 short (4 sentences), front-loaded with purpose, and efficiently covers key behavior. Slightly verbose in repetition but overall good conciseness.

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 presence of an output schema, the description adequately covers get vs generate, timing, and precondition. It does not discuss errors or edge cases, but for a simple tool this is sufficient.

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?

Input schema has 100% coverage with descriptions for all three parameters. Description adds minimal extra context (deal_id source, memo_type definitions) but mostly reiterates schema info, so baseline 3 is appropriate.

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 tool gets or generates an investment memo for a deal, with specific verbs and resource. It distinguishes from siblings by focusing on memo retrieval/generation, which is unique among tools like sieve_dataroom, sieve_deals, etc.

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 on when to use generate=false vs generate=true and mentions the prerequisite 'Requires a completed screen'. However, it does not explicitly state when not to use this tool or suggest alternatives.

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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