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get_function_logs

Retrieve recent logs from a deployed function, including console output and error stack traces from CloudWatch. Filter by project, function name, time range, or request ID.

Instructions

Get recent logs from a deployed function. Shows console.log/error output and error stack traces from CloudWatch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesFunction name to get logs for
tailNoNumber of log lines to return (default: 50, max: 1000)
sinceNoOnly return logs at or after this ISO 8601 timestamp (e.g. 2026-03-29T14:00:00Z). Invalid timestamps are rejected before the API call.
project_idYesThe project ID
request_idNoOnly return logs correlated to this routed request id, function run id, or attempt id, such as req_abc123, fnrun_abc123, or fnatt_abc123.
Behavior3/5

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

No annotations are present, so the description carries the full burden. It mentions the log source (CloudWatch) and types of output, but does not disclose any side effects, authorization requirements, or data limits beyond what the schema implicitly states. Adequate but not rich.

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 extremely concise (one sentence, 18 words) and front-loaded with the core action. While brief, it communicates the essential purpose without waste.

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

Completeness3/5

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

For a tool with 5 parameters and no output schema, the description is minimal. It does not explain the return format or distinguish from the closely named sibling 'get_function_run_logs'. The core behavior is covered, but gaps remain for complete agent understanding.

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% with detailed parameter descriptions. The description adds no additional meaning to the parameters. At baseline 3, it neither improves nor degrades the understanding.

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 tool retrieves recent logs from a deployed function, specifying the content (console.log/error output, stack traces). However, it does not differentiate from the sibling tool 'get_function_run_logs', which could cause confusion for the agent.

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?

No guidance is provided on when to use this tool versus alternatives like 'get_function_run_logs'. The description merely states what it does, missing explicit when/when-not usage context.

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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