Check the progress of a Sieve analysis.
Returns which IMPACT-X dimensions are complete with their scores, overall progress percentage, and current phase.
Args: deal_id: The deal ID returned by sieve_screen.
| Name | Required | Description | Default |
|---|---|---|---|
| deal_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as read-only and non-destructive. The description adds value by specifying exactly what information is returned (dimensions, scores, progress percentage, phase), which is not disclosed in the annotations. It does not contradict 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded. The first sentence states the purpose, the second explains the output, and the Args section adds necessary parameter context. There is no redundant fluff relative to the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a single parameter, clear output description, and an output schema, the description is complete for an agent to select and invoke the tool. It provides enough context about the input source and expected results without needing additional explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does so by explaining that deal_id is the ID returned by sieve_screen, providing important context for where to obtain the value. This is sufficient for a single simple parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: checking the progress of a Sieve analysis. It specifies the resource (Sieve analysis) and the action (check progress), distinguishing it from sibling tools like sieve_screen and sieve_results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the usage context by stating the deal_id comes from sieve_screen, indicating this tool should be used after screening. However, it does not explicitly exclude alternatives or mention other tools for different purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.
