submit_task
🤖 BrowserGPT Agent: submit task
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | Specific parameters for this action. |
🤖 BrowserGPT Agent: submit task
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | Specific parameters for this action. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure, and it discloses nothing: no mutation semantics, no auth requirements, no side effects, no return behavior. 'Submit' implies a write action but nothing confirms what it affects or whether it is reversible.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, but brevity here reflects under-specification rather than efficient conciseness. A single emoji-prefixed fragment earns no informational place and front-loads nothing an agent can act on.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and no usage or behavioral detail, the definition is completely inadequate for a task-submission tool that sits alongside related session and tracking tools. An agent has no basis for deciding to call it or predicting its effect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There is only one parameter and schema description coverage is 100%, so per the baseline rule the schema itself does the documenting work. The description adds no meaning about what 'detail' should contain, but the high coverage keeps this at the baseline rather than lower.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description is essentially a restatement of the tool name: 'BrowserGPT Agent: submit task' adds no verb-object specificity beyond what 'submit_task' already conveys. It does not distinguish this from siblings like track_task or converse, so an agent cannot tell what submitting a task actually accomplishes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to use this tool versus converse, track_task, or get_session_history. No preconditions, no alternatives, no context — the agent must guess from the name alone.
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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