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Modelmeter

by xyz.modelmeter

check_model_dependencies

Is my stack okay? Check a list of model ids against the record: scheduled retirements with days-remaining countdowns and migration targets, past retirements, and other breaking/action-required changes. Id matching tolerates dots vs dashes, dated snapshot suffixes, and bare or provider-prefixed forms. Call this at startup or in CI with the models you depend on.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYesModel ids to check, e.g. ["gpt-4o", "claude-sonnet-4-6", "gemini-2.5-flash"].

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description takes full burden. It discloses tolerance for ID variations (dots vs dashes, suffixes, prefixes) and what it checks (scheduled retirements, past retirements, breaking changes). However, it does not explicitly state it is read-only or describe failure modes.

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?

Three sentences, front-loaded with purpose, no filler. Every sentence adds value: purpose, behavior, usage. Excellent conciseness.

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?

The description covers purpose, matching logic, and usage. Lacks explicit output description (no output schema), but for a check tool with one array parameter, it is adequately complete for an agent to understand and invoke.

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% with an example. The description adds significant semantic meaning by explaining the purpose of the parameter and the matching logic, going beyond the schema's basic type and example.

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 checks model IDs against retirement records, with a friendly opener 'Is my stack okay?' The verb 'Check' and resource are explicit, and it distinguishes from siblings like list_deprecations by focusing on specific models.

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 advises calling 'at startup or in CI with the models you depend on,' providing clear usage context. It does not explicitly exclude alternatives or contrast with siblings, but the guidance is strong.

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

A3.9/5.0
Disambiguation4/5

Tools are mostly distinct, but list_deprecations and list_events overlap in covering deprecations. Descriptions clarify that list_deprecations is specific to retirement schedules with runways, while list_events is a broader changelog filterable by severity, so an agent could still choose correctly.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case (e.g., list_models, get_model, estimate_cost). The length variation is minor and does not break the pattern.

Tool Count5/5

Seven tools is an ideal size for this domain—enough to cover key operations (listing, getting details, checking dependencies, estimating costs, viewing history) without overwhelming the agent. Each tool has a clear role.

Completeness4/5

The tool set covers the main use cases for model information and monitoring. A minor gap is the lack of a dedicated tool to list providers, though list_models can filter by provider name. Overall, CRUD-like coverage is good for a read-heavy informational server.

Resources