Tulina

apify_run_status

Read-only

Check a run: status (READY, RUNNING, SUCCEEDED, FAILED, TIMED-OUT, ABORTED), defaultDatasetId (where the output is) and usageTotalUsd (what it cost so far).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "run_id": "<run_id>"
    },
    "name": "apify_run_status"
  }
}

Input Schema

Name	Required	Description
`_org`	No	Org (id) de CET APPEL. `oto_list_orgs()`.
`_group`	No	Équipe (id) de CET APPEL, sous son org parente.
`run_id`	Yes
`_run_id`	No	OBLIGATOIRE à chaque appel dès `run_start` ou `data_claim_next` : sans lui, l'écriture sur une ligne réservée est refusée. Hérité seulement si le serveur tient un run actif — n'y compte pas.
`_project`	No	Projet (id) de CET APPEL — jeton PRIMAIRE. `oto_project(op='list')`.
`_instance`	No	Instance de connecteur PRÉCISE (un credential exact). `oto_instance(op='list')`.
`wait_for_finish`	No

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

B3.1/5.0

Behavior3/5

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

The readOnlyHint annotation already establishes safe read-only behavior. The description adds useful output details absent from any output schema, but it does not explain wait_for_finish behavior, long-running polling semantics, or what happens when a run is unavailable.

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 a single front-loaded sentence with no wasted words, and the returned fields are listed compactly. It is appropriately sized for a status-check tool.

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

Completeness3/5

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

The description covers the primary output fields, which is important because there is no output schema. However, it leaves out wait_for_finish semantics and does not help the agent choose between polling, waiting, syncing, or aborting.

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?

With seven parameters and only 71% schema description coverage, the description adds no parameter-level meaning. In particular, wait_for_finish has no schema description and is not explained in the tool description, leaving an important behavioral parameter undocumented.

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?

The description gives a clear verb-resource pair, "Check a run," and enumerates the key fields returned: status with its possible values, defaultDatasetId, and usageTotalUsd. It distinguishes itself from apify_abort_run by being a status check, though it does not explicitly contrast with apify_run or apify_run_sync.

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 guidance, no mention of prerequisites, and no comparison with alternatives such as apify_run_sync or apify_abort_run. The only implied usage is checking an existing run, which is minimal.

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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