Mostly Right

List the small models a recipe can call

list_models

Read-onlyIdempotent

Lists the small models this deployment serves to recipes, by task: classify (label each row of a text column with yes/no or choice questions), extract (pull named, verbatim-grounded fields out of page or document text) and match (link the same entity across tables; planned until it is served). Returns {tasks: [{task, status, what, bindings, note?}], reference}. status is available, not_served, planned or unknown. Each binding carries its route (origin, method, path), its pinned model, max_requests_per_second, usage_today, quota, and a request_template for a per-row source: copy origin, method, path_template and model exactly, because the platform credential is chosen by that route and pin. Each also carries a pages_template (request_timeout_seconds 120, retries 3) to write into the collection's pages: the model service scales to zero and can take three to five minutes to start, and the run waits that out. A binding with for_recipes false is listed for completeness and never written into a recipe. The person enrols no key and pays nothing for these calls. Call it once per conversation before the brief, and offer what it lists where the table would gain from it; the build skill's references/enriching-with-small-models.md says when. Next: suggest_enrichments after a run.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_models"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 23, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare read-only and idempotent, and the description adds genuinely new behavior: full return shape, the four status values, the cold-start penalty (3-5 minutes to scale from zero, run waits it out), the for_recipes=false exclusion rule, and the no-key/no-cost guarantee. This is close to complete; only rate-limit enforcement semantics for max_requests_per_second are left implicit.

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?

Front-loaded with purpose and routing, then descends into operational detail in a sensible order. It runs long and a few clauses (the nested pages_template parenthetical) are dense, but nearly every sentence carries actionable information for a tool with no output schema.

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?

With zero parameters and no output schema, the description must carry the entire contract, and it does: field names, status enum, binding structure, template-copy rule, timeout/retry values, and the recipe-writer exclusion. An agent can invoke it and correctly consume the result from this text alone.

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?

The tool takes no parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The space it would occupy is instead spent on return-value semantics, which the schema cannot carry because there is no output schema.

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?

States a specific verb and resource ('lists the small models this deployment serves to recipes') and then enumerates the three capability families it reports on (classify, extract, match). An agent can distinguish it from catalog_search or list_recipes without opening any schema.

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?

Gives an explicit cadence ('call it once per conversation before the brief'), an explicit decision rule for acting on the result ('offer what it lists where the table would gain from it'), a pointer to the deeper guidance file, and a named next step (suggest_enrichments after a run).

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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