agentjido/jido_run/llm-db

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Builder-oriented guidance for the upstream `llm_db` package. Use when Codex needs to model provider and model catalogs, select models by capability or price, wire catalog lookups into Elixir code, or review `llm_db` boundaries versus `req_llm`, `jido`, and `jido_ai`.

Install

npx vskill@latest install agentjido/jido_run/llm-db

SKILL.md

LLM DB

llm_db is the upstream Hex package name.

Start Here

Use this skill when the task is about model metadata, capability catalogs, or provider/model selection logic.

Good triggers:

  • "Add model selection based on context window or pricing."
  • "Normalize OpenAI, Anthropic, or OpenRouter model ids in Elixir."
  • "Turn the LLM DB docs into a runnable catalog lookup example."
  • "Review whether this code belongs in llm_db or in the provider client."

Read references/builder-notes.md before editing when the task touches capability filters, pricing metadata, or cross-provider normalization.

Primary Workflows

Build catalog-backed selection
  • Model the caller's selection criteria first: provider allowlist, modality, tool support, context window, price ceiling, or local-vs-hosted constraint.
  • Keep catalog lookup pure and deterministic. Return model metadata or a narrowed candidate list before making any network call.
  • Push actual inference requests into req_llm or another provider client. llm_db should decide, not execute.
Add or refine provider metadata
  • Start from the package's existing schema and naming conventions instead of inventing a parallel shape.
  • Preserve upstream provider ids exactly, then add a local mapping layer only if the app needs aliases.
  • Prefer additive metadata updates over app-specific branching in the core catalog.
Turn docs into runnable examples
  • Build examples around lookup, filtering, ranking, or capability checks.
  • Show how the chosen model metadata feeds a later req_llm or Jido workflow.
  • Keep examples small enough to run in iex or a focused test.
Review package boundaries
  • Keep catalog concerns in llm_db.
  • Keep request transport, retries, and streaming in req_llm.
  • Keep agent orchestration, directives, and tool use in jido or jido_ai.

Build Checklist

  • Confirm which providers and model families the app actually needs.
  • Verify whether the task needs static metadata, live pricing refresh, or both.
  • Keep the API shape obvious: input criteria in, ranked models or metadata out.
  • Add tests for provider aliases, missing models, and fallback behavior.

Boundaries

  • Do not use this skill for prompt design or message shaping.
  • Do not hide provider-specific HTTP logic inside catalog helpers.
  • Do not promise pricing freshness beyond what the package sources actually support.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
44
Repository forks
20
7-day trend score
19

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 17 May 2026, 5 months ago.

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