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Apply Change Set

apply_change_set

Apply a staged change set to the app. Creates a Saved Version before applying. Blocks on validation errors unless force=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNoApply even if validation has errors
app_idYesThe app ID
change_set_idYesChange set ID

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only indicate non-read-only and non-destructive, so the description carries the burden. It adds two important behaviors: it 'Creates a Saved Version before applying' and 'Blocks on validation errors unless force=true.' These go beyond annotation hints and inform the agent of side effects and conditional behavior, though it does not mention post-application state (e.g., whether the change set is consumed).

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?

Two sentences, no filler. The core action and key side effect are front-loaded, and the blocking condition is stated compactly. Every phrase earns its place.

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 mutation tool with no output schema, the description covers the essential behavior (apply, create Saved Version, block on errors), and the schema covers parameters. It does not mention prerequisites like needing an existing change set, but the phrase 'staged change set' implies that. Considering the simple tool complexity and that sibling validate_change_set exists, it is sufficiently complete, though it could hint at the recommended workflow (validate before apply).

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 descriptions cover all three parameters (app_id, change_set_id, force) at 100% coverage, so the description adds little parameter-level detail. The only extra is the phrase 'Blocks on validation errors unless force=true,' which reiterates the force parameter's role. This meets the baseline but adds minimal value beyond the schema.

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 action ('Apply a staged change set to the app') and distinguishes itself from sibling lifecycle tools like discard_change_set by noting the side effect of creating a Saved Version. The verb and resource are specific, and it reads as a distinct operation among the change-set siblings.

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 implies the tool is for applying a previously staged change set and mentions blocking on validation errors, which gives context for when to use it (after validation). However, it does not explicitly reference siblings like validate_change_set or discard_change_set, so alternatives are not spelled out. Still, the usage context is clear enough for an agent to infer the right moment to call it.

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

B3.4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions, but there are some overlapping pairs like read_app_file/read_app_files and create_entity_records vs seed_entity, which could cause misselection. Singular/plural variants and compatibility tools introduce minor ambiguity, but the majority are well-separated.

Naming Consistency4/5

Tool names predominantly follow a consistent verb_noun pattern (e.g., create_app, get_entities, delete_secret). There are some variations like 'agency_create_client' and 'seed_entity' that deviate slightly, but the overall convention is predictable and readable.

Tool Count2/5

With 82 tools, the server is far above the typical range and feels overwhelming. Even for a full platform API, the count is extreme and likely increases selection complexity. A more curated set would improve navigability without sacrificing capability.

Completeness5/5

The tool surface is exceptionally comprehensive, covering app lifecycle, file operations, entity CRUD, versioning, A/B testing, secrets, integrations, domains, agents, scheduling, policies, and member management. No obvious missing operations for the platform's scope; it even includes validation and workflow guidance tools.

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