Sieve

sieve_screen

Run a Sieve IMPACT-X Quick Screen on a startup.

Analyzes the company across 7 dimensions (Innovators, Market, Product, Advantage, Commerce, Traction, X-Factor) and returns an analysis ID. Takes 2-5 minutes to complete. Upserts -- if the company was previously screened, returns the existing deal (set confirm=true to re-screen).

Two ways to use:

v3 (recommended): First add documents with sieve_dataroom_add, then call sieve_screen(deal_id=...) to analyze everything in the data room.
v2 (legacy): Call sieve_screen(company_name=..., website_url=...) directly. At least one of website_url or pitch_deck_text is required in this mode.

Args: company_name: Name of the startup to screen (v2 flow, or to create new deal). deal_id: Screen an existing deal by ID (v3 flow -- use after sieve_dataroom_add). website_url: Company website URL (v2 flow). pitch_deck_text: Extracted pitch deck text (v2 flow). description: Brief company description (optional). confirm: Set to true to re-screen an existing deal.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`confirm`	No
`deal_id`	No
`description`	No
`website_url`	No
`company_name`	No
`pitch_deck_text`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A5/5.0

Behavior5/5

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

The annotations (readOnlyHint=false, openWorldHint=true) are consistent with the description. The description goes beyond annotations by disclosing the upsert behavior, the 2-5 minute runtime, and that it returns an analysis ID. It also explains the re-screen behavior with confirm=true, providing valuable context about side effects without contradicting the annotations.

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 well-organized and front-loaded with the core purpose. It uses a clear hierarchy: summary, key facts, usage modes, and argument details. Each sentence adds value with no redundancy, making it efficient despite covering complex functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity—six parameters, two workflows, an output schema, and relationship to sibling tools—the description covers all necessary aspects: purpose, prerequisites, behavioral notes, arguments, and return value. It even references sieve_dataroom_add for the v3 flow, making it fully self-contained for selection and invocation.

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

Parameters5/5

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

The schema has 0% description coverage, but the description compensates fully with a detailed 'Args' section. Each parameter is explained with its usage flow (v2 vs v3), constraints (e.g., required fields), and optionality. This is essential since the schema alone provides no parameter descriptions.

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's purpose: 'Run a Sieve IMPACT-X Quick Screen on a startup.' It specifies the action, resource, and scope, and differentiates itself from siblings by describing two distinct workflows (v3 with deal_id and v2 with company details). This makes the purpose unambiguous and distinguishable from related tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when and how to use the tool, including two usage modes with a clear recommendation (v3 first after sieve_dataroom_add, v2 as legacy). It also explains the condition for re-screening (confirm=true) and the requirement for at least one of website_url or pitch_deck_text in v2, giving agents clear decision-making criteria.

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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TDQS

A4.5/5.0

Disambiguation5/5

Each tool serves a distinct role in the screening workflow: dataroom listing vs adding, deal listing, screening, status polling, results retrieval, memo generation, and usage checking. No two tools have overlapping purposes.

Naming Consistency4/5

All tools share the 'sieve_' prefix, but the pattern is inconsistent: some are pure nouns (sieve_deals, sieve_results), one combines resource and action (sieve_dataroom_add), and one is a verb (sieve_screen). Still, the names are readable and predictable once the domain is understood.

Tool Count5/5

With 8 tools, the set is well-scoped and covers the entire lifecycle of a startup screening operation without unnecessary bloat. Each tool earns its place.

Completeness4/5

The core workflow is complete: add documents, screen, check status, retrieve results, generate memo, and list deals. Minor gaps exist, such as no update/delete for data room documents or a dedicated deal detail view, but agents can work around these.

Resources

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