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Get Job Status

get_job_status
Read-onlyIdempotent

Check the status of a deployment job. STATUS VALUES: pending (job queued), running (deployment in progress), completed (success), failed (deployment failed). TIMELINE: Typical deployment takes 2-5 minutes. If status is 'running' for >10 minutes, check get_project_info for detailed pod status. If status is 'failed', use get_project_info to see deployment errors and check schema format (must be FLAT, no 'fields' nesting).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob ID returned from deployment operations

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds meaningful behavioral context: expected deployment duration (2-5 minutes), status semantics, and guidance on handling prolonged or failed states. It surfaces potential pitfalls (schema format) and recommended follow-ups, which is genuine additional value.

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 well-organized with clear labels (STATUS VALUES, TIMELINE) and each sentence carries useful information. It is slightly longer than the absolute minimum but remains readable and efficient. The front-loaded purpose sentence followed by structured details earns a strong score, though minor trimming could make it even tighter.

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?

For a simple one-parameter, read-only status tool with no output schema, the description is remarkably complete. It covers status semantics, expected timing, abnormal conditions, and specific next actions. The annotations handle safety, and the description fills all practical usage gaps, making it fully self-sufficient for an agent.

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?

The input schema already describes job_id as 'Job ID returned from deployment operations' with 100% coverage. The description does not add syntactic details about the parameter, but it does provide context about deployment jobs (statuses, timelines). This meets the baseline for high schema coverage without needing extra parameter elaboration.

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 clearly states the tool's function: 'Check the status of a deployment job.' It also enumerates the status values (pending, running, completed, failed), making the specific resource and operation unambiguous. This distinguishes it from sibling tools like get_project_info, which provides broader project details.

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?

Explicit guidance is provided for when to use this tool versus alternatives. The description instructs to check get_project_info when status is 'running' for >10 minutes or when 'failed', and even prescribes checking schema format in failure cases. This clearly delineates the tool's scope and escalation paths.

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

A3.8/5.0
Disambiguation4/5

Most tools are clearly differentiated by domain (project vs graph_project) and action (create, get, list, delete). The main ambiguity is get_project vs get_project_info, which both claim to return detailed project information. Otherwise tool boundaries are clear.

Naming Consistency4/5

The server follows a strong verb_noun convention, with parallel naming for graph and non-graph tools (create_project/create_graph_project, deploy_staging/deploy_graph_staging). Minor deviations include bulk_create_graph_nodes and fulltext_search_graph, but patterns remain predictable.

Tool Count2/5

48 tools is a heavy surface, even when accounting for the two parallel product domains (relational and graph). Many tools are near-duplicates across domains, and the count exceeds the 25-tool threshold that feels manageable. It would benefit from consolidation or sub-servers.

Completeness4/5

Both project types have full life-cycle coverage: create, schema management, deployment, rollback, and deletion, plus graph data operations including bulk, search, and traversal. Minor gaps exist, such as no update_graph_relationship and the redundant get_project/get_project_info pair, but agents can accomplish core workflows.