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Glama

Kirk — Unsupervised Structural Change Detection

by io.github.UlyssesModel

List Kirk Models

kirk_list_models
Read-only

Enumerate the model_ids the sealed engine exposes, with the engine sha stamped in-response.

Purpose: Discover the model catalog and record the sealed engine sha alongside your inference results.

Use when: You are wiring a client for the first time and need model_id values for kirk_score_book / kirk_score_book_batch calls, or you want a machine-readable catalog with attestation.

Do not use when: You need per-model hyperparameter detail — those are intentionally not exposed on the customer surface.

Capability class(es): C5 (engine sha attested on every response).

Path fit: Validation via MCP (this tool). Production integrations run in-process under sealed-engine attestation — same binary sha as this endpoint. Contact Kavara for deployment options.

Cost: 0 IU. Free tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark readOnly/destructive hints, and the description adds engine-sha attestation, capability class C5, zero cost, and a same-binary-sha guarantee, going well beyond the structured fields. 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?

Structured with short labeled sections, front-loaded purpose, and each line (use cases, exclusions, path fit, cost) carries distinct value. No redundant filler.

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?

Covers purpose, use vs non-use, attestation behavior, cost, and integration path; output schema explains the return shape, so no gaps. The sibling context reinforces this is the discovery tool for the score_book family.

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?

Tool has zero parameters and the input schema is fully self-contained (100% coverage), so baseline 4 applies; no parameter-level documentation is necessary or provided.

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 opening sentence uses a specific verb ('Enumerate') and resource ('model_ids the sealed engine exposes'), immediately differentiating this catalog tool from inference/billing siblings. It also defines the response's attestation component.

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 provides 'Use when' and 'Do not use when' conditions, including when wiring a client for score_book calls and when hyperparameter detail is needed. The path-fit note distinguishes MCP validation from production in-process use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Kirk — Unsupervised Structural Change Detection toolsInspect
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TDQS

A4.7/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose: billing (checkout/show/usage), scoring (single/batch/legacy/synthetic/random), utility (health/models/bulk_howto/render/research). Descriptions are detailed enough to prevent confusion.

Naming Consistency5/5

All tools follow a consistent 'kirk_<domain>_<verb>' pattern (e.g., kirk_billing_checkout, kirk_score_book). No mixing of conventions or unpredictable names.

Tool Count5/5

12 tools is well within the optimal range. Each tool serves a specific need without redundancy, covering scoring, billing, health, models, and research.

Completeness5/5

The tool surface covers the full workflow: scoring (single/batch/legacy/synthetic/research), billing (checkout/balance/usage), health checking, model listing, tensor prep, and bulk client generation. No obvious gaps for the intended domain.

Resources