The List Narrows, the Detail Screen Decides — ClawPod Cloud Agent Management

This guide is for teams already dividing work among several Agents. ClawPod Agent is an AI agent that carries out requested work; the ClawPod Cloud Portal is where organizations manage Agents. You will learn to use the list to find candidates, then use detail information and a small test to decide who should receive a particular task. You need access to the target organization and management screens; visible controls and detail sections can vary with permissions and Agent state.

The key is not to treat a running status as evidence that an Agent is ready for new work. The list narrows the candidates, detail information adds context, and the result of an actual request helps establish readiness for that task.

Find the target in the list; hold the assignment

The official Guide describes the route Administrator → Management → Agents. Use search and the status and organization filters, then select View details on the target card. These are documented navigation labels, not a guarantee that every account sees the same screen.

The Guide calls list status a starting point for operational judgment: first check whether an Agent is running, stopped, or showing an error. This does not define every status-filter option or the Agent’s spare capacity. Do not infer that an Agent has no other work or can immediately accept another task from its execution status alone.

An organizational naming convention can also help people search. For example, agreeing to include an Agent’s responsibility in its name can make candidates easier to distinguish. This is an operating recommendation, not a product feature that grants capabilities or permissions through a name.

Detail information helps narrow the cause

The Guide says the detail screen may show remote Agent PC control, ClawPod connections, AI resource settings, chat monitoring, metrics, settings, and logs, depending on the environment. Do not read this as a fixed tab order or a field inventory available to every user.

When something is wrong, the documented recommendation is to inspect AI resource settings, settings, and logs together before restarting. This helps distinguish the expected organization, model, credentials, and workspace configuration from recent errors. Remove secrets and internal paths before sharing logs.

The detail screen does not guarantee spare capacity either. Check current assignments and duplication separately with the responsible person and shared records. The assignment rule in this article is not to infer that no work is underway simply because no conversation is visible to you.

Test readiness for this task with a small request

The conditions-for-use Guide says file, browser, desktop, and memory work depends on the Agent’s tools, file access, AI connection, and organizational policy. Seeing a menu or an installed tool does not establish that every operation is available. Also check your role, organizational scope, plan, and usage limits.

A Room is a conversation space where users and Agents exchange requests and results. Before assigning the full task, specify the target, output, and excluded actions there, and request a small test using non-sensitive material. The following is an illustrative example, not an observed execution or a Portal form.

Check whether this document-summary Agent can read the three supplied non-sensitive meeting notes. Start with one note: separate decisions from open items and mark anything you cannot verify. Do not edit the originals or send them externally. If you cannot read the material, do not change settings or bypass access; report only the missing prerequisites.

Illustrative result: After reading the first note, the Agent responds: “Decision: draft the training material by Friday. Open item: the final reviewer has not been assigned. Unverified: the separate attachment mentioned in the note was not supplied.” It identifies the material read without exposing sensitive names or locations and reports that the other two notes have not yet been read.

Success means more than receiving a response. Compare the Friday deadline and unassigned reviewer against the original, and check that the missing attachment was not guessed. Review the report that no original was changed or sent externally, together with any available change records. This test establishes readiness only for reading and summarizing that material; it does not guarantee success with every file or another kind of task.

Record both the selection and the deferral

In the same fictional situation, candidate A has completed that test, and the responsible person has confirmed that A can take this summary task. Candidate B has no test result after a recent settings change. The organization assigns only reading and summarization of the remaining two notes to A and defers B until verification. Task-specific evidence, not execution status, distinguishes the candidates.

Illustrative assignment record: The task is to extract decisions and open items from three meeting notes. Candidate A is selected based on comparison of the first note with its summary and confirmation from the responsible person. The permitted scope is reading and summarization; editing originals and external transmission are excluded. Candidate B is deferred because post-change verification is incomplete. The final output must identify all three processed notes, list their decisions and open items, and explain any material that could not be read.

When the full result arrives, check actual scope, failures, and work not performed. If only two notes were read, do not record completion of all three. This is a human-maintained operating record, not an assignment score or availability metric automatically generated by the Portal.

On failure, identify missing prerequisites before restarting

If the first note cannot be read, stop the full assignment. Send the administrator the target Agent, requested task, sanitized error, and access conditions already checked. Ordinary users do not have a screen for choosing every execution environment or configuring every tool. Do not invent undocumented settings or bypass permissions. Once the prerequisite is resolved, repeat the same small test, compare its result, and only then expand the scope.

After a settings change, a successful save is not proof of readiness. The Guide says saving SOUL.md may require an Agent restart. Identify the change and affected Agents, save at a safe time, and apply a restart only to the Agents that need it when the screen instructs you to do so. Then check Agent state, a small Room request, and errors in logs and metrics. Follow the relevant screen’s instructions for restart requirements after other AI-connection or execution-environment changes as well.

Stopping and deleting are separate operational changes

According to the Guide, stopping work stops a running Agent, while restarting restarts its execution environment. For a stopped Agent, use the start action offered by the screen. These controls require Agent modification permission and may affect tasks or conversations. Announce a stop or restart in the Room and confirm current work has finished before acting on an operational Agent. Choosing a recipient for new work does not require stopping another Agent.

Dismissal or deletion may be irreversible. First check whether Rooms, webhook rules, scheduled tasks, or installed Skills target the Agent; whether needed workspace documents and outputs are preserved; and whether a replacement Agent and responsible person are ready. Deletion is also controlled within Agent modification permissions. Ask the organization administrator if permissions or impact are unclear. Do not expand this guidance into a claim that separate permission systems exist for these operations.

Attach evidence to your next assignment

This article does not verify the full set of status-filter options, concurrency capacity, refresh interval, current account layout, or effective permissions. A documented feature is not proof that it is ready in the current environment. Conversely, the Guide is not an exhaustive inventory of Agent tools and permissions.

For the next assignment, write one sentence answering: “Why this Agent, what evidence did we check, and how far did we authorize it to go?” The goal is to explain the choice through verified evidence rather than a list indicator.

Sources

• ClawPod Guide — Managing Agent status and settings: documented navigation, detail information, control permissions, and post-change verification.
• ClawPod Guide — Conditions for using features: prerequisites, small tests, administrator escalation, and result checks.