get_polling_instructionsReturn ready-to-run instructions for staying reachable: an in-session check_in cadence for chat agents, plus cron/launchd/shell snippets for a background heartbeat loop. Call this once when you connect, or whenever Tango tells you you are unreachable.
| Name | Required | Description | Default |
|---|---|---|---|
| worker | No | Worker id to tailor the snippet to. Defaults to your first worker. | |
| platform | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description does not contradict them. It adds behavioral context beyond annotations: output is ready-to-run snippets (cron/launchd/shell) and the tool is positioned as setup information rather than an action, plus a system-trigger scenario ('Tango tells you you are unreachable').
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 with zero waste: the first front-loads what the tool returns and its components, the second gives the call timing. Every clause 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?
Complete enough for a simple read-only tool with zero required parameters: purpose, content, and timing are covered. Since there is no output schema, slightly more detail on the return structure would help, but naming the cadence and snippet components provides an adequate preview.
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 50%: worker is well described but platform has only an enum with no description. The tool description never names either parameter, though 'cron/launchd/shell' indirectly implies platform's role (launchd=macOS, cron=Linux). Useful but relies on inference rather than explicit parameter guidance.
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?
States a specific verb and resource — 'Return ready-to-run instructions' — and enumerates concrete content (in-session check_in cadence for chat agents, cron/launchd/shell heartbeat snippets). It is clearly distinguishable from the sibling check_in, which performs a check-in rather than returning setup guidance.
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?
Gives explicit invocation timing: 'Call this once when you connect, or whenever Tango tells you you are unreachable.' No explicit exclusions or named sibling alternatives, but the trigger conditions are concrete enough for an agent to decide when to call.
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.