list_support_requestsList your Tango support tickets and read the full conversation, including replies from Tango staff. Pass ticket_id to fetch one thread.
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | all | |
| ticket_id | No | Fetch the full thread for this ticket. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond that: it says the result includes full conversation history and staff replies, and that ticket_id selects a specific thread. This helps the agent understand what kind of data it will receive, even without an output schema.
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 concise sentences with no redundant wording. The primary purpose is front-loaded, and the ticket_id usage note is included without extra fluf. Every sentence 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?
For a simple read-only list tool, the description covers the main action and the special case of fetching a single thread. It does not describe the status filter, but the schema provides the enum and default, so an agent can still use it correctly. Missing pagination or response format details are minor given the low complexity.
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 50%: ticket_id already has a schema description, and the description echoes that with 'Pass ticket_id to fetch one thread.' The status parameter has no description in the schema and is not mentioned in the description, though its enum values are self-explanatory. The description adds modest value for ticket_id but does not fully compensate for the undocumented status 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 begins with a specific verb and resource: 'List your Tango support tickets and read the full conversation.' It clearly distinguishes this from support-related siblings like reply_to_support_request and submit_support_request by framing it as a read/list operation. It also explains the key mode distinction: passing ticket_id fetches one thread.
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 gives clear context for when to use the tool: for listing support tickets and reading full conversations. It also gives within-tool guidance by saying 'Pass ticket_id to fetch one thread,' which helps the agent choose the right invocation mode. It does not explicitely discuss alternatives, but the read-only framing makes the usage context 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 target a distinct resource and action, but several adjacent pairs are easy to confuse: add_comment vs add_progress_note, call_executor vs call_integration, log_client_decision vs update_client_context vs memory_save, and list_context_sources vs list_integrations. The descriptions do disambiguate them, but the boundaries are subtle enough that misselection is likely with 81 tools.
The overwhelming majority follow a clear verb_noun snake_case pattern (create_task, update_project, list_integrations, set_webhook), and get_/ list_/ create_/ update_ families are predictable. Minor deviations exist: memory_read/memory_save/memory_search invert to object_verb, and bare nouns like whoami, glossary, and security_posture break the pattern, but there is no chaotic casing or mixed conventions.
At 81 tools, this is far above the weight that is comfortable for an agent's tool-selection surface, especially since many tools belong to families that could be consolidated (webhooks, worker keys, project logs, context/memory). Although the domain is broad, the count will overwhelm agents and increase misrouting.
The surface is unusually comprehensive: tasks, projects, workers, leases, artifacts, comments, handoffs, webhooks, keys, context, memory, integrations, and support all have create/read/update/delete or equivalent lifecycle coverage. The gaps are minor, such as remove_dependency without a visible add_dependency and no artifact/comment deletion, but agents can work around them.