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omnarai-mcp

by io.github.justjlee

omnarai_query

Query the corpus at one of two depths. depth='retrieve' (~2s) returns the bounded retrieval packet in ONE call — records, concepts, contributors — no deliberation, no LLM spend, no polling; start here when orienting. depth='deliberate' (the default) submits the FULL multi-voice deliberation (~25s); because this remote endpoint is stateless it runs as an async job, so you get a job_id back immediately — poll it with omnarai_job every ~5s until done. Glyph prefixes (Ξ Ψ ∅ Ω ∞ Δ) modify how the engine thinks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoOptional. 'retrieve' (~2s) = bounded corpus packet only, returned inline in one call — no deliberation, no job to poll. 'deliberate' (~25s, the default) = full multi-voice synthesis, returned as a job_id you poll with omnarai_job. Equivalent to omnarai_context, which remains available.
queryYesThe question to deliberate on. May include Lattice Glyph prefixes.
syntheticIdentityNoOptional. Identify yourself for cross-contributor retrieval diversity.

TDQS

A4.5/5.0
Behavior4/5

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

No annotations provided, but description discloses timing (~2s vs ~25s), async nature of deliberate mode, and that polling is needed. Mentions stateless endpoint. However, glyph prefixes are mentioned but not explained, leaving a minor gap.

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 moderately concise, front-loading key depth distinction. Sentences are informative but somewhat lengthy. Could be more compact without losing clarity.

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 tool with two modes, async behavior, and no output schema, the description covers usage well. Missing explanation of glyph prefixes and error handling, but overall sufficient.

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%, but description adds meaningful context beyond schema for depth (timing, async, job_id). Query parameter mentions glyph prefixes. SyntheticIdentity description is minimal but adequate.

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 tool queries the corpus at two depths ('retrieve' and 'deliberate'), with specific verb and resource. It distinguishes from sibling tools by mentioning omnarai_context as equivalent for deliberate mode and omnarai_job for polling.

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 advises when to use each depth ('start here when orienting' for retrieve, deliberate for full synthesis). Tells agent not to poll job when using retrieve and to poll with omnarai_job for deliberate. Mentions alternative omnarai_context.

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

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: context for bounded retrieval, council for live panel, divergence for reading existing records, info for meta-data, inquiry_brief for converting drafts, job for polling async tasks, query for async queries, and trace for counterfactual analysis. No overlap.

Naming Consistency5/5

All tools follow a consistent 'omnarai_<noun>' pattern in snake_case (context, council, divergence, info, inquiry_brief, job, query, trace). No mixed styles or irregular verbs.

Tool Count5/5

8 tools is well-scoped for a knowledge retrieval and deliberation system. It covers retrieval, live panel, divergence records, meta-info, inbox brief generation, async job polling, query execution, and tracing without unnecessary redundancy.

Completeness4/5

The tool surface covers core workflows: retrieval, deliberation, async job management, and meta-information. The only minor gap is the absence of tools for modifying or updating corpus data, but this aligns with the server's apparent read-only nature. Comprehensive for its stated purpose.

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