approval_session_get_approval_session_statusGetApprovalSessionStatus is a lightweight poll (status only) for the gated action to check whether it can proceed
| Name | Required | Description | Default |
|---|---|---|---|
| sessionId | Yes | UUID value wrapper. |
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | ||
| updatedAt | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it is a safe read operation. The description adds 'lightweight' and 'status only' which reinforce the non-mutating, poll-like behavior, but it does not disclose any additional behavioral details such as rate limits, authentication requirements, or what happens when the action cannot proceed. Still, given the annotation coverage, the description adds some value beyond the structured data.
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 a single, well-structured sentence that front-loads the tool's name (GetApprovalSessionStatus) and clearly communicates its purpose in a compact form. Every word adds value: 'lightweight,' 'poll,' 'status only,' and 'gated action' all contribute to understanding the tool's function without wasted prose.
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?
Given the tool's low complexity (one simple parameter), the presence of a read-only annotation, and an output schema (as indicated by hasOutputSchema=true), the description sufficiently covers the essential context. It tells the agent exactly what the tool checks and its lightweight nature, leaving no critical gaps for basic usage. The output schema presumably details the return values, so the description does not need to explain them.
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?
The input schema has one parameter, sessionId, with a description ('UUID value wrapper') that fully covers its meaning (100% schema description coverage). The tool description does not mention the parameter, so it adds no additional semantic value beyond the schema. This aligns with the baseline score of 3 when schema coverage is high.
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 with a specific verb ('poll') and resource ('approval session status'), and defines its scope as a lightweight, status-only check for whether a gated action can proceed. It effectively distinguishes itself by focusing on the approval session domain and its polling nature, leaving no ambiguity about what the tool does.
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 when to use the tool: when you need to poll the status of a gated action to see if it can proceed. It provides clear context by labeling it a 'lightweight poll,' but it does not explicitly mention alternatives or when not to use it, though no direct sibling tool exists for approval sessions, making this less critical.
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.
Multiple tool pairs are nearly identical (formation_extract_cap_table / formation_extract_cap_table_ocr; formation_start_formation / formation_create_formation), and several tools lack descriptions, making selection ambiguous. The scale of 202 tools with overlapping summaries (e.g., multiple cap-table summary tools) compounds the confusion.
Dominant snake_case `module_verb_noun` pattern, but with notable deviations: `captable_send_safe_for_signature` uses an inconsistent abbreviation, `check_company_name_availability` lacks a module prefix, and `get_list_` vs `list_` prefixes are mixed. Readable but not fully consistent.
202 tools is far beyond any reasonable surface for a single server, even a broad platform. The sheer number overwhelms and makes tool discovery impractical; many tools are peripheral (ads metrics) to the core formation purpose.
The domain appears well covered: formation flows, cap-table lifecycle (import, close, simulate), accounting (journal entries, periods, schedules), cards, documents, and transactions all have CRUD or lifecycle operations. Minor gaps exist (e.g., no card deletion, no counterparty creation), but they are unlikely to cause dead ends.