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ai·rete·rag

by com.ai-rete-rag

Ingest policy text

ingest_text

Add policy/reference text to a domain's knowledge base.

The text is chunked and embedded; explanations for future decisions in this domain will cite it. Creating a new domain claims it for your account (plan limits apply). The built-in demo domains are read-only — ingest into your own domain instead. On team plans, only the domain admin (the member who created the domain, or the subscription owner) can add documents.

Args: domain: Domain to ingest into (existing or new). text: The policy or reference text. source: Optional source name shown in the document list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
domainYes
sourceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.8/5.0
Behavior5/5

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

It discloses several important behaviors beyond the annotations: text is chunked and embedded and will be cited in future decisions, creating a new domain claims it with plan limits, demo domains are read-only, and team plans have admin-only ingestion. The readOnlyHint=false and destructiveHint=false are consistent with the description, and there's no contradiction.

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?

The description is well-structured and suitably sized: a clear first sentence, followed by essential behavioral context, then a compact Args section. Every sentence earns its place without unnecessary verbosity.

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?

The description covers side effects, permissions, parameter semantics, and usage constraints. Since an output schema exists, return-value details are not required. It is complete for a tool of this complexity.

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

Parameters5/5

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

The schema has 0% description coverage, but the Args section fully explains each parameter: domain (existing or new), text (policy/reference text), and source (optional name shown in document list). This adds meaning beyond the schema's bare titles and types.

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 opens with a clear, specific verb and resource: 'Add policy/reference text to a domain's knowledge base.' This distinguishes it from sibling tools like import_policy_rules, which likely handle structured rules rather than free text. The rest of the description reinforces the purpose by explaining how the text is processed and used.

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 gives useful context: demo domains are read-only and users should ingest into their own domain, and team plans require admin permissions. However, it does not explicitly mention alternative tools or when to choose this over import_policy_rules, so it stops short of the full 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

A4.3/5.0
Disambiguation5/5

Each tool serves a clearly distinct purpose: decide executes decisions, rule management tools (get_rule_source, list_rules, put_rules) each address different aspects of rule viewing/editing, import_policy_rules handles policy-to-rule drafting, and document tools handle knowledge base content. No two tools are easily confused.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern, e.g., list_rules, get_usage, put_rules, import_policy_rules. The single-verb 'decide' fits naturally as the core action. There is no mixing of styles or unpredictable naming.

Tool Count5/5

With 8 tools, the server is well-scoped for its purpose of rule-based decisioning with RAG support. Each tool represents a distinct capability in the workflow—policy ingestion, rule authoring, knowledge base management, decision execution, and usage monitoring—without excess.

Completeness4/5

The tool set covers the core lifecycle: ingest policy text, import draft rules, publish rules, list rules/source, and execute decisions. Minor gaps exist such as no explicit delete for documents or rules (though put_rules with empty YAML can effectively clear rules), and domain listing is indirect via list_rules. These are workable omissions.

Resources