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templetwo
by templetwo

nape_observe

Manually inject tool-call details into Nape's record, triggering automatic drift detection for monitoring and testing.

Instructions

Manually inject a tool-call observation into Nape's record. Most observations will come from an automatic hook in the main dispatcher in a future release. Use this tool for manual injection and testing. Drift detection runs automatically after each observe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tool_nameYesName of the tool that was called.
argumentsNoArguments passed to the tool.
resultYesString representation of the tool result.
session_idYesCurrent session identifier.
Behavior2/5

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

No annotations are provided, so the description must cover behavioral traits. It mentions drift detection runs automatically after observe, but does not detail what drift detection does, potential side effects, or required permissions. The description is insufficient for a safe understanding of the tool's behavior.

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 three sentences long, front-loaded with the core action, and each sentence provides essential information without redundancy.

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?

No output schema is provided, and the description does not mention what the tool returns (e.g., success/failure message). It also lacks error handling or edge-case information, leaving the agent without a complete picture.

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?

Schema coverage is 100%, so the description does not need to add much. The description does not elaborate on parameter interactions or constraints beyond the schema, meeting the baseline but not exceeding it.

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 clearly states the specific action: 'Manually inject a tool-call observation into Nape's record.' It distinguishes this tool from the automatic hook, making its purpose unambiguous.

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

Usage Guidelines4/5

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

The description explains when to use this tool: for manual injection and testing, as automatic hooks will handle most cases. This provides clear usage context, though it does not explicitly list alternatives.

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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