List additional forms attached to a Lever opportunity.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Results per page. Lever accepts 1-100; default is endpoint-specific. | |
| cursor | No | Lever pagination offset token from a previous response. Use next_cursor from the prior tool result. | |
| opportunity_id | Yes | Lever opportunity ID. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It only states that it lists forms, without mentioning pagination (despite the limit/cursor parameters), read-only nature, response shape, or the meaning of 'additional'. This is insufficient for a complete behavioral understanding.
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 sentence, front-loading the action and resource with no redundant words. However, the term 'additional' is vague and could be more explicit, which prevents a perfect score for clarity within conciseness.
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 no annotations and no output schema, the description leaves critical gaps: it does not explain what 'additional forms' means, what the response structure looks like, or how pagination works. The schema covers parameters but not the overall behavior, and the description fails to compensate.
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 coverage is 100% with descriptive text for all three parameters (limit, cursor, opportunity_id). The description itself adds no parameter-specific context, so it meets the baseline for high schema coverage without needing to compensate.
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 states the action ('List'), the object ('additional forms'), and the parent scope ('a Lever opportunity'). It is distinct from sibling tools like get_opportunity_form (singular) and list_form_templates (not opportunity-attached), though the word 'additional' is ambiguous and not fully clarified.
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?
No guidance is provided on when to use this tool versus alternatives such as get_opportunity_form or list_opportunity_notes. There are no exclusions, prerequisites, or explicit use-case context, so the agent cannot infer the appropriate selection criteria beyond the tool name.
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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Most tools target distinct resource-action combinations, but the sheer count (108) and the presence of closely related tools like list_opportunity_feedback / get_opportunity_feedback may cause occasional agent confusion.
Tool names follow a highly consistent verb_noun pattern (e.g., create_*, get_*, list_*, update_*, delete_*, add_*, remove_*). Minor exceptions like apply_to_posting still fit the overall structure.
With 108 tools, the surface is excessively large for most agent workflows. Many tools could be merged or removed without losing essential functionality, leading to decision overload.
The tool set covers the full Lever API surface comprehensively, including opportunities, postings, requisitions, users, webhooks, templates, files, and compliance data, leaving no obvious gaps.