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jobs_status

Read durable job state and progress by job ID for Android and iOS security audits to prevent interrupted workers from being reported as successful.

Instructions

Read durable job state and progress. An interrupted worker never becomes a successful audit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.3

TDQS

C2.4/5.0
Behavior1/5

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

The description asserts a pure read operation ("Read durable job state and progress"), but the annotations declare readOnlyHint=false, meaning the tool may modify state. That is a direct contradiction of the behavioral claim in the text. The remaining sentence adds no concrete behavior such as polling cadence, terminal state semantics, or error conditions.

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

Conciseness3/5

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

Two short sentences, front-loaded with the action, which is good. The second sentence is atmospheric and ambiguous rather than informative, so it does not clearly earn its place in a definition this terse.

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

Completeness2/5

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

An output schema exists, so return values need not be explained, but for a job-polling tool the description omits the essential context: how the job_id is obtained, how to interpret completion vs. failure, and how this differs from jobs_list. Combined with the annotation contradiction, this leaves the agent under-informed.

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?

Schema description coverage is 0% for the single job_id parameter, and the description says nothing about its format, or where the id comes from (presumably audit_start or jobs_list). The name is largely self-explanatory, which prevents a 1, but the description does nothing to compensate for the missing schema documentation.

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

Purpose4/5

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

"Read durable job state and progress" states a specific verb (Read) and resource (job state/progress), so the core purpose is unambiguous. It does not, however, distinguish itself from sibling job tools such as jobs_list or jobs_cancel, leaving the agent to infer the boundary from the name alone.

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

Usage Guidelines2/5

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

There is no explicit when-to-use, when-not-to-use, or alternative guidance. The agent must infer that this is called after audit_start to poll a job, and the cryptic line "an interrupted worker never becomes a successful audit" reads as an aphorism rather than a usage rule. None of jobs_list, jobs_cancel, or audit_scan are referenced as alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.