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stackdiff
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Structured diff showing what would be deployed if the user ran tfdeploy now. Returns component-level changes (added/removed/modified), field-level details, and pricing deltas.

Defaults (#1392): with no version arguments, compares the LAST SUCCESSFULLY DEPLOYED version against the user's CURRENT LIVE DESIGN (the same data the UI shows). Empty baseline if nothing has been deployed or after a destroy. Pending drafts are NOT used as the target — they go stale once the user edits past them; live IR via chat history is always current.

Pass explicit from_version and/or to_version integers to compare any two saved versions (e.g. v3 → v5).

REQUIRES: session_id from convoopen response (format: sess_v2_...).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
to_versionNoEnding stack version number for the diff. Defaults to the current draft.
from_versionNoStarting stack version number for the diff. Defaults to the latest applied version.

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint, but the description adds substantial behavioral detail: the return structure (component/field/pricing changes), default comparison semantics, the fact that pending drafts are not used, and the `session_id` credential requirement. These go well beyond the annotations and clarify tricky state-dependent behavior.

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 compact and organized: a top-line summary, a defaults paragraph, an explicit-version sentence, and a requirement line. The reference to '#1392' is minor noise but does not detract significantly. Overall, it is appropriately sized with no wasted sentences.

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 compensates by explaining what the tool returns (component-level changes, field-level details, pricing deltas). It also covers default behavior, state-dependent baselines, and required credentials, making it sufficiently complete for an agent to invoke 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?

Schema description coverage is 100%, with each parameter already well-documented (defaults, types, patterns). The description reinforces the defaults for from_version/to_version but adds no new semantic detail beyond the schema. This meets the baseline of 3 for high schema coverage.

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 states a specific verb+resource: 'Structured diff showing what would be deployed if the user ran tfdeploy now.' It clearly distinguishes from siblings like stackversions (listing versions) and tfplan (planning a run), making the tool's 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?

Provides clear context for when to use: to preview deployment impact, with defaults comparing last deployed version to current live design. It also explains edge cases (empty baseline before deployment or after destroy) and prerequisites (session_id). However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.

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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