List all issues for a task list (event). Returns open, acknowledged, and resolved issues with severity, type, and category. Use this to discover issues that need AI analysis via tascan_analyze_issue.
| Name | Required | Description | Default |
|---|---|---|---|
| list_id | Yes | Task list (event) ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds behavioral context beyond this by stating the scope ('all issues'), the statuses included (open, acknowledged, resolved), and the fields returned (severity, type, category). This is meaningful, though it does not cover pagination or authorization.
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 two sentences, front-loaded with the action and resource, followed by a useful downstream-use note. Every sentence earns its place with no redundancy or filler.
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?
For a simple one-parameter read-only tool with rich annotations, the description fully covers what the tool does, what it returns, and why it is used (to feed into tascan_analyze_issue). It is well-suited to guide an AI agent in selecting and invoking the tool.
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 list_id described as 'Task list (event) ID'. The description repeats this term but does not add further parameter-level details. Therefore, the schema carries the parameter semantics, and the description adds no extra value beyond the baseline.
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 uses a specific verb-resource pair ('List all issues for a task list (event)') and clearly distinguishes from siblings like tascan_list_tasks (tasks vs issues) and tascan_list_events (events only). It further specifies the returned data (open, acknowledged, resolved issues with severity, type, category), making the purpose unmistakable.
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 provides a clear usage context: 'Use this to discover issues that need AI analysis via tascan_analyze_issue.' This implicitly guides the AI to use this tool before analysis. It lacks explicit exclusions or alternatives, but the intended workflow is clear.
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.
Most tools map to a distinct resource+action pair, and the descriptions clearly separate entities like tasks, subtasks, workers, invoices, zones, assets, and reports. A few close pairs (get_report vs generate_report, dispatch_instruction vs dispatch_to_agent, analyze_issue vs auto_resolve) require careful reading, but the descriptions are detailed enough to disambiguate them.
The vast majority follow a tascan_verb_noun pattern with consistent create/get/list/update/delete verbs. Minor deviations like condition_history, server_info, zone_compliance, and one-word find slightly break the otherwise predictable pattern.
At 69 tools, this is far beyond what an agent can efficiently consider, and it bundles several distinct domains into one MCP surface. Even if each tool is individually useful, the combined set is an extreme mismatch for a coherent tool interface.
The surface covers nearly the full lifecycle for projects, events, tasks, subtasks, workers, reports, invoices, zones, assets, issues, and communications. Minor gaps exist (no explicit asset updates/decommissioning, no cancel_invite, no delete_zone), but the main workflows have no dead ends.
