AALY

update_field

Idempotent

Update a field's behavior or metadata. MUTABLE (change any time): label, description, default_value, required, hidden, min, max, pattern, values. IMMUTABLE: type, unique, search, targets, multiple, valueType, computed, stored, formula. Passing ANY of these — even mixed with mutable ones in the same call — rejects the WHOLE call atomically with NOTHING applied; update_field never silently drops or partially applies an immutable attribute, so only pass attributes you actually intend to change (don't echo back a full field record from list_fields). To actually change one: create a differently-named field with the correct shape and migrate data into it per-tenant via direct REST calls — do NOT delete_field + create_field under the same name, that leaves stale data readable under the old shape. Run the migrate-field prompt for the full step-by-step recipe, or see the aaly://platform/capabilities resource, 'Known footguns'. Note: there is no separate 'facet' attribute at all (create_field has no such param) — faceting is automatic whenever search:true is set on an eligible type, so it follows search's own immutability.

Input Schema

TableJSON Schema

Name	Required	Description
`max`	No	For text: max char length. For number: max value. For list/multiple: max items.
`min`	No	For text: min char length. For number: min value. For list/multiple: min items.
`label`	No
`hidden`	No	Excludes the field from GET responses (write-only). Purely a read-time flag.
`values`	No	For enum fields: replace the list of allowed string values. Removing a value already stored on existing records doesn't corrupt them — it only stops new writes from using it.
`pattern`	No	For text fields: regex the value must match. Violations return 400 PATTERN_MISMATCH.
`field_id`	Yes	Field record ID (e.g. 'FLD12')
`required`	No	Only affects future POSTs; does not re-validate existing records.
`description`	No
`default_value`	No	Match the field's own type — a JSON boolean for type 'boolean', a JSON number for type 'number', a string otherwise.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations cover only idempotency and non-destructiveness; the description adds substantial behavior the schema can't express: whole-call atomic rejection when any immutable attribute is passed, no silent drops/partial applies, stale-data-readable footgun from delete+recreate, and automatic faceting tied to search immutability. Rich context well beyond structured fields.

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?

Front-loads the highest-value content (MUTABLE/IMMUTABLE lists and the atomicity warning) so an agent gets the critical constraint first. Dense but justified given the footgun complexity, though the trailing 'facet' note is somewhat tangential.

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?

For a mutation tool with no output schema, it covers atomicity, immutability constraints, migration guidance, and even corrects a likely false assumption about a 'facet' attribute. An agent has everything needed to invoke it safely.

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

Parameters4/5

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

Schema coverage is 80%, so the schema already documents individual params, but the description adds critical meaning the schema lacks: the mutable/immutable partition (type, unique, search, targets, etc. are immutable) and the atomic-rejection rule for mixing them. This is genuine semantic value, though per-parameter syntax is left to 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?

States a specific verb+resource ('Update a field's behavior or metadata') and immediately distinguishes itself from sibling tools by enumerating which attributes are mutable vs immutable. An agent can tell it apart from create_field/delete_field without opening any schema.

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?

Explicitly says what not to do (don't echo back a full field record, don't delete_field+create_field under the same name), the atomicity consequence, and names the precise alternatives (create a differently-named field and migrate per-tenant, the `migrate-field` prompt, the capabilities resource). Nothing is left to inference.

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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