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laserfiche_field_values_get

Retrieve template field values for a Laserfiche entry by providing its entry ID. Returns metadata such as status, reviewer, or signing date.

Instructions

Read the template field values currently on an entry.

Use after you have an entry ID and need the metadata fields the user is asking about — e.g. "what's the status of this form?", "who's the assigned reviewer?", "when was this signed?". For the entry's own properties (name, type, path), use get_entry instead.

Args: entry_id: Integer entry ID.

Returns: {"values": [...]} — a list of field-value descriptors under the values key. Each item has field_name, values (always a list, even for single-value fields), field_type, is_multi_value, and is_required. Empty / unset fields are typically omitted by the Repository API rather than returned with empty values, so an empty list usually means the entry has no template assigned.

On failure: returns {"mode": "error", "error": <slug>, "entry_id": <int>, ...}. Common slugs: not_found, auth_failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entry_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations exist, so description carries full burden. It fully describes return format under 'values' key, each field item structure, empty/unset field handling (omitted by Repository API), and failure modes with error slugs. This is comprehensive behavioral disclosure.

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?

Description is well-structured with separate sections for purpose, usage, args, returns, and errors. Each sentence adds value, though slightly verbose in the returns section. No fluff.

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?

Given a single parameter and presence of output schema, description covers all necessary context: when to use, output structure details, empty behavior, and failure modes. No gaps.

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

Parameters2/5

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

Schema has 0% description coverage for the only parameter 'entry_id'. Description adds only 'Integer entry ID' which adds minimal meaning. With no schema description, this is insufficient; should provide more context like expected range or source of entry ID.

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?

Description states 'Read the template field values currently on an entry' with specific verb and resource. Distinguishes from sibling tools like 'get_entry' by clarifying that 'For the entry's own properties (name, type, path), use get_entry instead.'

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 'Use after you have an entry ID and need the metadata fields the user is asking about' with concrete query examples. Also provides negative guidance: 'For the entry's own properties, use get_entry instead.'

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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