Search the organization's work-structure entities (customers, projects, tasks, subtasks, users) by id or name. Returns a flat, assignment-scoped result list.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum results to return (default 30). | |
| query | Yes | Search text — matches by entity id (prefix) and name (contains). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It explains matching behavior (id prefix, name contains) and result structure (flat, assignment-scoped). However, it does not disclose further behavioral traits like order, case sensitivity, or read-only nature.
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?
Two sentences efficiently convey purpose and result format with no wasted words. The description is front-loaded and earns its place.
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?
The tool has no output schema, so the description should compensate. It covers entity types and search matching but omits details like result fields, order, and the meaning of 'assignment-scoped'. This leaves some gaps for an agent.
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 parameter descriptions. The description adds minimal semantic value beyond restating the search method. Baseline for high coverage is 3.
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 searches work-structure entities by id or name and returns a flat result list. It uses a specific verb and resource, and while it does not explicitly differentiate from siblings, its cross-entity scope is distinct among the listed siblings.
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 usage for finding entities by id/name but lacks explicit guidance on when to use this tool versus specific list tools or other search tools. No when-not or alternatives are provided.
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 tools have overlapping purposes, e.g., create_time_report and log_time both create a single time entry with near-identical descriptions. There are also many similar getter/list tools that blur together, making it hard for an agent to select the right one.
Most tool names use snake_case, but verbs are inconsistent: 'list' vs 'get' for similar operations, 'manage' combines create/update/delete, and 'use_favorite' is an outlier. This pattern reduces predictability.
With 114 tools, the set is extremely large and far beyond a well-scoped server (typical 3-15). This overwhelms agents and suggests many tools could be consolidated or removed.
The tool surface covers a broad domain including customers, projects, tasks, time tracking, invoicing, and user management, but there are gaps like no list_users or direct user listing, and some operations seem redundant rather than filling missing functionality.