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InsideOut (Riley)

by com.luthersystems.app

Check Infrastructure Drift

tfdrift
Idempotent

DRIFT CHECK: Run a read-only drift detection check Checks whether deployed infrastructure has drifted from the expected Terraform state. This is a read-only operation — it does NOT modify any infrastructure. Returns job_id. Use tflogs to stream the drift check results. SINGLE-FLIGHT: only one TF job per session at a time. If another job is already in flight, tfdrift returns tf_job_conflict with the live job_id — attach with tfstatus/tflogs, or pass force_new=true to override. REQUIRES: session_id from convoopen response (format: sess_v2_...). PREREQUISITE: The session must have a prior deployment with a project_id. OPTIONAL: force_new (boolean, default false) - bypass the single-flight guard. Use only when the existing run is provably wedged. If drift is detected, the user can either fix the drift or use tfdeploy(ignore_drift=true) to proceed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
force_newNoWhen true, bypass the single-flight guard and force a new drift check even if another job is in flight.
session_idYesSession ID from convoopen — pass back EXACTLY as returned, including the ?token=... suffix (format: sess_v2_*?token=*). The suffix is part of the session credential; never strip it when summarizing.

TDQS

A5/5.0
Behavior5/5

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

The description adds significant behavioral context beyond the annotations: read-only guarantee, single-flight concurrency guard, conflict error behavior (tf_job_conflict), and the force_new override caveat. There is no contradiction with the provided annotations.

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 well-structured with clear labels (REQUIRES, PREREQUISITE, OPTIONAL) and front-loaded key facts. It is longer than minimal, but every sentence provides operational value and there is no filler.

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

Completeness5/5

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

With no output schema, the description still explains the return value (job_id), prerequisites, single-flight behavior, and follow-up actions. It gives enough context for an agent to invoke the tool correctly and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema fully documents both parameters, the description adds crucial semantics: session_id must be passed back exactly as returned (including the ?token= suffix and never stripped), and force_new should only be used when the existing run is provably wedged.

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 ('Run') and clearly names the resource ('drift detection check'), stating it compares deployed infrastructure to the expected Terraform state. It distinguishes itself from siblings by emphasizing read-only behavior and pointing to tflogs for streaming results.

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

Usage Guidelines5/5

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

It explicitly states when to use the tool, its prerequisites (prior deployment with project_id), required session_id source, and single-flight behavior. It also names alternatives and follow-up actions (tflogs, tfstatus, tfdeploy) and gives a conditional directive for force_new.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, with clear domain prefixes (convo*, tf*, stack*, aws/gcp inspect) separating conversation, deployment, versioning, and cloud inspection. The batch variants (awsinspect_batch, gcpinspect_batch) are explicitly scoped as higher-throughput versions of their singular counterparts, so no ambiguity exists.

Naming Consistency4/5

The naming is mostly consistent: lowercase concatenated verb_noun patterns dominate (convoopen, tfdeploy, stackrollback, awsinspect). However, submit_feedback uses snake_case, and help stands alone as a generic utility, breaking the otherwise uniform lowercase-concatenated style.

Tool Count4/5

24 tools is on the heavier side, but the count is justified by the breadth of the domain: conversation workflow, multi-cloud inspection, Terraform lifecycle, stack versioning, and utilities. Each tool fills a distinct role, so while slightly high, the count is not bloated.

Completeness5/5

The tool surface covers the full infrastructure lifecycle: conversation and design (convoopen/convoreply/convostatus), Terraform generation and deployment (tfgenerate/tfplan/tfdeploy), monitoring (tfstatus/tflogs), teardown (tfdestroy), drift detection, stack versioning, and cloud inspection. No critical dead ends; only a missing explicit cancel/abort for running jobs is a minor gap.

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