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Update Single-Task Agent

lyzr_agent_update_single_task
Idempotent

Update an existing single-task agent by its ID with new configuration such as name, model, provider, and prompts.

Instructions

Update a single-task template agent by id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesAgent name
modelYesModel name, e.g. "gpt-4o"
top_pYesNucleus sampling probability
agent_idYesAgent id to update
agent_goalNoThe agent's goal
agent_roleNoSystem/role prompt for the agent
descriptionNo
provider_idYesLLM provider id, e.g. "openai"
temperatureYesSampling temperature
extra_fieldsNoAdditional SingleTaskAgentConfig fields to merge into the body
llm_credential_idNoCredential id for the LLM provider
agent_instructionsNoTask instructions for the agent
Behavior2/5

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

Annotations already declare this as a mutating, idempotent, non-destructive operation, but the description adds no behavioral context such as whether the update is partial or full, which fields are required, or what happens to omitted fields. This is a significant gap for an update operation.

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 a single concise sentence with no filler words, making it front-loaded and easy to parse. However, it is under-specified, sacrificing completeness for brevity.

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?

For a 12-parameter mutation tool with no output schema, the description is too sparse. It omits update semantics (partial vs. full), required fields' behavior, and return value format. The schema covers parameters but not the behavioral context needed for correct invocation.

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?

With 92% schema description coverage, the schema already documents most parameters clearly. The description adds no additional parameter semantics, so it does not improve on the schema but also does not detract from it.

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 clearly states the verb ('Update') and resource ('single-task template agent by id'), which distinguishes it from sibling tools like lyzr_update_agent and lyzr_agent_create_single_task. However, 'template agent' is not defined, leaving some ambiguity about what exactly is updated.

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 guidance on when to use this tool versus alternatives such as lyzr_update_agent or lyzr_agent_create_single_task. The description implies usage by naming the resource, but it lacks explicit context, prerequisites, or exclusions.

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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