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Get Job Status

get_job_status
Read-only

Poll a pending tool call by its jobId. Each poll either returns the final result (succeeded/failed/cancelled), or reports the call as still running — call it again until you get the result. Failed calls return their stored error message. A jobId belongs to exactly ONE task: it never blocks other tools or other jobs (run them freely in parallel), and once terminal it is frozen history — a NEW user request means a fresh call on the originating tool, never re-polling an old jobId. Legacy v!/b! job ids are also accepted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYes
wait_secondsNo

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses detailed behavior: each poll returns a terminal state or 'still running', failed calls return stored errors, jobId uniqueness, non-blocking concurrency, frozen history after terminal, and acceptance of legacy ids. This adds significant value beyond the structured annotations.

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

Conciseness4/5

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

The description is ~100 words, front-loaded with the core purpose, and each sentence adds relevant detail. It is slightly dense with many clauses but remains efficient and well-structured, earning a 4 for conciseness rather than verbosity.

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

Completeness4/5

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

The description covers return behavior (terminal states, error messages) and usage context (concurrency, history, legacy ids), which is essential. However, it omits any explanation of the optional wait_seconds parameter, a gap that prevents full completeness for callers. Otherwise it's quite thorough.

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

Parameters2/5

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

The schema provides no descriptions for jobId or wait_seconds, and the description only explains jobId (as the identifier of the polled job). The optional wait_seconds parameter is completely unmentioned, leaving agents without guidance on how it affects polling. With 0% schema coverage, the description must compensate but only partially does.

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 precise verb ('Poll') and resource ('a pending tool call by its jobId'), and clarifies the operation's nature as polling for result. It distinguishes itself from sibling tools like cancel_request by focusing on status retrieval, not cancellation or other actions.

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

Usage Guidelines4/5

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

The description gives clear when-to-use guidance: poll pending calls and repeat until terminal. It also specifies when NOT to use it (new user request should trigger a fresh call, not re-poll). However, it does not explicitly name alternative tools, though siblings like get_publish_status exist; the guidance is still sufficient for routing.

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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TDQS

A3.6/5.0
Disambiguation4/5

Tools are mostly distinct, but there is some overlap among file-modifying tools (edit_file, write_file, apply_patch) and between run_code_in_vm and run_code_in_browser. Detailed descriptions and clearly scoped use cases help agents select correctly.

Naming Consistency4/5

Most tools follow a verb_noun snake_case pattern (create_project, list_files, execute_sql), but a few deviate (apply_patch, card_upload_asset, run_code_in_vm). Overall readable and predictable, with only minor inconsistencies.

Tool Count2/5

With 46 tools, the server exceeds the typical well-scoped range and approaches the extreme threshold. While the broad scope of a full development platform justifies many tools, this count may overwhelm agents and increase misselection risk.

Completeness4/5

The tool surface covers the full development lifecycle: project creation, file operations, database management, resource provisioning, deployment, testing, and debugging. Minor gaps exist (e.g., no delete_project or checkpoint management), but core workflows are well-supported.

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