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search_entries

Execute a raw Laserfiche search query to retrieve matching entries, specifying syntax with braces and operators for precise filtering.

Instructions

Run a raw Laserfiche search query and return matching entries.

Use when you already know how to express the search in Laserfiche query syntax. If the user describes what they want in natural language and you are unsure how to translate, prefer search_natural (which asks the server for the available templates and field names first). For a simple name-pattern lookup, search_by_name is the cheaper option.

Query syntax cheat sheet:

  • {LF:Name="Onboarding*"} — name pattern (* and ? wildcards)

  • {[Loan Application]:[Last Name]="Smith"} — field on template

  • {LF:LookIn="\Imports\2024"} — restrict to a folder subtree

  • Combine with & (AND) / | (OR), e.g. {LF:Name="*.pdf"} & {[Application]:[Status]="Approved"}

Args: query: A Laserfiche search expression. Quote string values with double quotes; escape inner quotes by doubling them. max_results: Page size (default 25, capped by LF_MAX_RESULTS_CEILING, typically 200).

Returns: SearchResults with entries (id, name, entry_type, full_path), total_count, and next_link. Drill in with get_entry or get_field_values.

On failure: returns {"mode": "error", "error": <slug>, ...} instead of raising. Slugs you might see here: server_error (most common, the SimpleSearches endpoint is fragile on some self-hosted builds — see search_natural for a more resilient path), auth_failed, rate_limited. Full taxonomy in docs/error-contract.md.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesLaserfiche search expression. Each clause wrapped in braces and combined with `&` (AND) or `|` (OR). Quote string values with double quotes; escape inner quotes with `\"`.
max_resultsNoPage size. Defaults to LF_MAX_RESULTS_DEFAULT (25). Capped at LF_MAX_RESULTS_CEILING (typically 200).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, so description bears full burden. It details return format (SearchResults with fields), error handling (returns error object with slugs), and mentions server fragility. Full disclosure of failure modes and their meanings.

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?

Well-structured with usage guidelines first, then cheat sheet, then parameter details. Each sentence adds value, though slightly lengthy. Could be marginally shorter but efficient overall.

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?

Complete for a search tool: describes return format (even without output schema), error handling, and sibling relationships. No notable gaps given the complexity and existing schema coverage.

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 100%, baseline 3. Description adds value by providing extra examples, clarifying maximum results cap, and explaining quoting rules in more plain language than schema. Not essential but beneficial.

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 it executes a raw Laserfiche query and returns entries, using specific verb 'run' and resource. It distinguishes from siblings by explicitly contrasting with search_natural and search_by_name.

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?

Explicit when-to-use (knowing query syntax), when-not (natural language or simple name), and provides alternatives with reasoning (search_natural for natural language, search_by_name for cheaper name lookup). Also includes a query syntax cheat sheet.

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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