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Get Run Status

get_run_status
Read-onlyIdempotent

Poll a search started by run_ugc_agent on the web app. Call it about 30 seconds after run_ugc_agent (or the previous get_run_status) returned status 'running' or 'queued', with the same list_id. While running it returns found_so_far and target; when the run is complete, ended, stopped, or no_run it returns the creators, the stop reason and a short explanation of why a run ended short. Read-only and cheap: poll every 30 seconds until the status is terminal, then present the creators and app_url.

Input Schema

NameRequiredDescriptionDefault
uidNoOptional Firebase uid. Must match the URL uid unless local fallback is enabled.
list_idNoThe list_id returned by run_ugc_agent. Falls back to conversation_id when omitted.
bearer_tokenNoOptional Firebase ID token. Hosted clients normally authenticate with an API key in the Authorization header or ?uid= in the URL instead.
conversation_idNoCreator-list key for durable state. Reuse a returned list_id for follow-ups; when omitted, MCP uses the active generated list for this tool chain.
preferences_modeNoHow to apply preferences for this call: 'stored' uses users/{uid}.agentPreferences, 'override' uses agent_preferences only, and 'none' disables stored filtering for this run.
agent_preferencesNoOptional per-call filtering preferences. Use with preferences_mode='override'. For backwards compatibility, passing this without preferences_mode implies override.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already establish that this is a safe read-only, idempotent, non-destructive operation. Beyond that, the description explains the polling behavior, what is returned while running (found_so_far and target), what is returned on terminal states (creators, stop reason, short explanation), and that the call is cheap, which is valuable because no output schema exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by timing, return behavior, and polling guidance. Despite being a single dense paragraph, every sentence contributes operational information and there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description appropriately explains the return behavior for both running and terminal states. It also covers polling cadence and when to stop, while the fully documented schema handles the remaining parameter details, so the definition is complete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all six parameters, including uid, list_id, bearer_token, conversation_id, preferences_mode, and agent_preferences. The description adds only limited parameter meaning by reinforcing the list_id relationship to run_ugc_agent, which merits the baseline score rather than a higher one.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it polls a search started by run_ugc_agent. It clearly distinguishes this tool from run_ugc_agent, which starts the search, and from stop_run, which stops it, so an agent can identify the tool without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit timing and conditions: call about 30 seconds after run_ugc_agent or a previous get_run_status returned 'running' or 'queued', and reuse the same list_id. It also specifies polling every 30 seconds until the status is terminal, leaving little to inference.

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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