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read_example

Retrieve a specific LangSmith example by its ID, with optional dataset version or timestamp for historical state.

Instructions

Read a specific example from LangSmith.

Args: example_id (str): Example ID to retrieve as_of (str, optional): Dataset version tag or ISO timestamp

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofNoDataset version tag or ISO timestamp
example_idYesExample ID to retrieve
Behavior3/5

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

No annotations are provided, so the description must convey safety and side effects. It states 'Read', implying a non-mutating operation, but does not disclose error behavior, return format, or permissions. The as_of parameter is described but not its behavioral implications. For a simple read, this is borderline adequate.

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 appropriately brief and front-loads the core purpose in the first sentence. The Args list is redundant with the schema but is not verbose and maintains a clean docstring structure without waste.

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

Completeness4/5

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

For a simple retrieval tool, the description is largely complete: it states what it does and documents both parameters. The lack of an output schema is mitigated by the straightforward 'Read' semantics, though it does not explicitly describe the return payload. Overall, the context is sufficient for an agent to invoke it correctly.

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?

The input schema covers both parameters fully (100% coverage), and the description's Args section replicates the same descriptions without adding new meaning. As a result, the description adds no semantic value beyond the schema, warranting the baseline score.

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

Purpose5/5

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

The description uses a specific verb ('Read') and specifies the resource ('a specific example from LangSmith'), clearly distinguishing it from sibling tools like list_examples which enumerate examples. The scope is unambiguous and immediately actionable.

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

Usage Guidelines3/5

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

The intended use is implied: you need an example_id to retrieve a specific example. However, it does not explicitly state when to prefer this over list_examples or mention any alternatives or exclusions. The guidance is present but not explicit.

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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