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contributing

Contribute to the RubyLLM AI framework - set up the repo, run and record specs, work on conversations, individual AI operations, providers, protocols, Rails integration, and docs. Use when fixing a bug, building a feature, writing specs, or changing documentation in the RubyLLM c

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Contributing to RubyLLM

Read AGENTS.md at the repo root first: it has the ground rules, the command table, and the architecture constraints that archspec check enforces. This skill adds the step-by-step recipes.

Choose the layer

The public API covers conversations (Chat, Message, Tool, Agent, structured output, streaming, and loop control) and individual operations (paint, animate, speak, transcribe, ocr, moderate, embed, and rerank). Both connect to services through providers and protocols: providers supply endpoints, authentication, catalogs, and protocol selection; protocols implement formats and their dialects.

Model resolution, configuration, accounting, instrumentation, batches, and provider resources support the framework as a whole. Keep independent operations independent of Chat. Rails integration adds Active Record, Active Storage, Hotwire, jobs, and generators around the same Ruby API; it does not define a second conversation API.

The fast loop

bundle exec rspec --tag ~live          # unit tests only, no keys, seconds not minutes
bundle exec rspec spec/ruby_llm/chat_spec.rb:42   # one example
overcommit --run                       # what the commit hook will run

Run the fast loop while developing. Run overcommit --run before declaring anything done: it runs RuboCop (auto-correct), Flay (duplication), archspec (architecture), and the unit suite, and the commit fails if any of them do.

Working with cassettes

Specs tagged :live replay recorded provider traffic from spec/fixtures/vcr_cassettes. The cassette name derives from the example's full description, so renaming an example orphans its cassette.

To re-record after changing request shapes:

rake vcr:record[openai]            # deletes that provider's cassettes, reruns the suite
rake vcr:record[openai,anthropic]  # several providers
rake vcr:record[all]               # everything (long, needs many keys)

Recording needs real API keys in .env. To re-record a single spec, delete its cassette file and run the spec with the provider's key set.

Rules that bite:

A failing :live example deletes its own cassette on purpose. Do not "fix" a red spec by restoring the cassette; fix the code, then re-record.
Review every new or changed cassette for leaked keys and personal data before committing. The pre-commit hook runs gitleaks, but eyes first.
A spec that can neither replay (no cassette) nor record (no key) skips with a message naming the env var it needs. That is expected on a fork without keys.

Adding or changing a chat option

Add with_x to lib/ruby_llm/chat.rb (chainable, returns self).
Add the matching bare x class macro to lib/ruby_llm/agent.rb. The archspec build fails without it.
Thread the option through the Provider contract, never by referencing a concrete provider or protocol from Chat.
Implement per protocol in lib/ruby_llm/protocols/* (render_* for request payloads, parse_* for responses).
Spec it in spec/ruby_llm/chat_<x>_spec.rb; add live coverage over the matrix in spec/support/models_to_test.rb when providers differ.
Document it on the matching page in docs/_core_features/.

Working on an individual AI operation

Start with the public operation and its typed result. Keep the shared RubyLLM names consistent across providers.
Route service calls through the Provider contract and registered protocols. Keep request rendering, response parsing, and format quirks in protocols.
Reuse model resolution, configuration, usage accounting, and instrumentation where applicable. Preserve the operation's streaming or job lifecycle.
Test public behavior and protocol translation at their respective layers. Document the operation in its feature guide and keep its Getting Started example short.

Adding a provider

For smaller or emerging providers, ship a community gem instead of a core PR (the core bar is high, see CONTRIBUTING.md):

bundle exec ruby_llm provider-gem Acme --api-base https://api.acme.ai/v1

That scaffolds a complete gem with specs and CI. For an approved core provider:

script/generate-provider acme

Then make it real:

lib/ruby_llm/providers/acme.rb declares auth, API base, and which protocols it speaks (protocol :chat_completions, ...). If the provider has its own wire format, that format is a new protocol under lib/ruby_llm/protocols/, not code inside the provider.
Replace the scaffold's example capabilities with the provider's real ones, and identify the model-catalog source.
Register the provider in lib/ruby_llm.rb (the entrypoint is the only place concrete providers get wired in).
Record cassettes covering normal chat and streaming chat at minimum.
Document configuration in docs/_getting_started/configuration-providers.md.

Rails work

Rails specs run against the dummy app in spec/dummy; acts_as_chat and acts_as_message live in lib/ruby_llm/active_record/.
The Rails integration builds on the domain layer and the Provider contract only. It converts records with to_llm/from_llm; plain-Ruby objects never define those.
Preserve the Ruby conversation API on records, Active Storage attachment support, and the persisted message lifecycle used by Hotwire streaming and background jobs. Individual operations remain callable directly from Rails services and jobs.
Generators live in lib/generators/ruby_llm/ (install, upgrade, chat_ui, agent, tool, schema, provider). Their specs are tagged :generator and excluded from the pre-commit run; run them explicitly with bundle exec rspec --tag generator.
Check Rails-version compatibility across the matrix: bundle exec appraisal rails-7.1 rspec through rails-8.1.

Docs work

Pages live in docs/ under _getting_started, _core_features, _advanced, and _reference. Preview with docs/bin/serve.sh.
Voice: Rails guides. Second person, present tense, show the code before explaining it, motivate each feature with the problem it solves in one sentence. No em dashes, no hype, no "simply".
Lead with short, working public API examples. Show how features combine when it helps the reader build something. Keep the title, description, and "After reading this guide" opening; introduce concepts before adding a summary table.
Front-matter description becomes the page's llms.txt entry and social card text: one compelling sentence, no &, <, or >.
Cross-link with {% link _collection/page.md %}, never hard-coded URLs.
docs/_reference/available-models.md is generated; never edit it.

Before opening the PR

overcommit --run passes.
New behavior has specs; changed provider behavior has re-recorded cassettes, reviewed for secrets.
Public API changes are documented in docs/ and have RDoc.
The PR does one thing, references its approved issue, and explains the problem before the solution.

Lihat sumber ↗

Metadata berkas

name: contributing
description: Contribute to the RubyLLM AI framework - set up the repo, run and record specs, work on conversations, individual AI operations, providers, protocols, Rails integration, and docs. Use when fixing a bug, building a feature, writing specs, or changing documentation in the RubyLLM codebase.

Lihat teks asli

---
name: contributing
description: Contribute to the RubyLLM AI framework - set up the repo, run and record specs, work on conversations, individual AI operations, providers, protocols, Rails integration, and docs. Use when fixing a bug, building a feature, writing specs, or changing documentation in the RubyLLM codebase.
---

# Contributing to RubyLLM

Read AGENTS.md at the repo root first: it has the ground rules, the command table, and the architecture constraints that `archspec check` enforces. This skill adds the step-by-step recipes.

## Choose the layer

The public API covers conversations (`Chat`, `Message`, `Tool`, `Agent`, structured output, streaming, and loop control) and individual operations (`paint`, `animate`, `speak`, `transcribe`, `ocr`, `moderate`, `embed`, and `rerank`). Both connect to services through providers and protocols: providers supply endpoints, authentication, catalogs, and protocol selection; protocols implement formats and their dialects.

Model resolution, configuration, accounting, instrumentation, batches, and provider resources support the framework as a whole. Keep independent operations independent of `Chat`. Rails integration adds Active Record, Active Storage, Hotwire, jobs, and generators around the same Ruby API; it does not define a second conversation API.

## The fast loop

```bash
bundle exec rspec --tag ~live # unit tests only, no keys, seconds not minutes
bundle exec rspec spec/ruby_llm/chat_spec.rb:42 # one example
overcommit --run # what the commit hook will run
```

Run the fast loop while developing. Run `overcommit --run` before declaring anything done: it runs RuboCop (auto-correct), Flay (duplication), archspec (architecture), and the unit suite, and the commit fails if any of them do.

## Working with cassettes

Specs tagged `:live` replay recorded provider traffic from `spec/fixtures/vcr_cassettes`. The cassette name derives from the example's full description, so renaming an example orphans its cassette.

To re-record after changing request shapes:

```bash
rake vcr:record[openai] # deletes that provider's cassettes, reruns the suite
rake vcr:record[openai,anthropic] # several providers
rake vcr:record[all] # everything (long, needs many keys)
```

Recording needs real API keys in `.env`. To re-record a single spec, delete its cassette file and run the spec with the provider's key set.

Rules that bite:

- A failing `:live` example deletes its own cassette on purpose. Do not "fix" a red spec by restoring the cassette; fix the code, then re-record.
- Review every new or changed cassette for leaked keys and personal data before committing. The pre-commit hook runs gitleaks, but eyes first.
- A spec that can neither replay (no cassette) nor record (no key) skips with a message naming the env var it needs. That is expected on a fork without keys.

## Adding or changing a chat option

1. Add `with_x` to `lib/ruby_llm/chat.rb` (chainable, returns `self`).
2. Add the matching bare `x` class macro to `lib/ruby_llm/agent.rb`. The archspec build fails without it.
3. Thread the option through the `Provider` contract, never by referencing a concrete provider or protocol from `Chat`.
4. Implement per protocol in `lib/ruby_llm/protocols/*` (`render_*` for request payloads, `parse_*` for responses).
5. Spec it in `spec/ruby_llm/chat_<x>_spec.rb`; add live coverage over the matrix in `spec/support/models_to_test.rb` when providers differ.
6. Document it on the matching page in `docs/_core_features/`.

## Working on an individual AI operation

1. Start with the public operation and its typed result. Keep the shared RubyLLM names consistent across providers.
2. Route service calls through the `Provider` contract and registered protocols. Keep request rendering, response parsing, and format quirks in protocols.
3. Reuse model resolution, configuration, usage accounting, and instrumentation where applicable. Preserve the operation's streaming or job lifecycle.
4. Test public behavior and protocol translation at their respective layers. Document the operation in its feature guide and keep its Getting Started example short.

## Adding a provider

For smaller or emerging providers, ship a community gem instead of a core PR (the core bar is high, see CONTRIBUTING.md):

```bash
bundle exec ruby_llm provider-gem Acme --api-base https://api.acme.ai/v1
```

That scaffolds a complete gem with specs and CI. For an approved core provider:

```bash
script/generate-provider acme
```

Then make it real:

1. `lib/ruby_llm/providers/acme.rb` declares auth, API base, and which protocols it speaks (`protocol :chat_completions, ...`). If the provider has its own wire format, that format is a new protocol under `lib/ruby_llm/protocols/`, not code inside the provider.
2. Replace the scaffold's example capabilities with the provider's real ones, and identify the model-catalog source.
3. Register the provider in `lib/ruby_llm.rb` (the entrypoint is the only place concrete providers get wired in).
4. Record cassettes covering normal chat and streaming chat at minimum.
5. Document configuration in `docs/_getting_started/configuration-providers.md`.

## Rails work

- Rails specs run against the dummy app in `spec/dummy`; `acts_as_chat` and `acts_as_message` live in `lib/ruby_llm/active_record/`.
- The Rails integration builds on the domain layer and the `Provider` contract only. It converts records with `to_llm`/`from_llm`; plain-Ruby objects never define those.
- Preserve the Ruby conversation API on records, Active Storage attachment support, and the persisted message lifecycle used by Hotwire streaming and background jobs. Individual operations remain callable directly from Rails services and jobs.
- Generators live in `lib/generators/ruby_llm/` (install, upgrade, chat_ui, agent, tool, schema, provider). Their specs are tagged `:generator` and excluded from the pre-commit run; run them explicitly with `bundle exec rspec --tag generator`.
- Check Rails-version compatibility across the matrix: `bundle exec appraisal rails-7.1 rspec` through `rails-8.1`.

## Docs work

- Pages live in `docs/` under `_getting_started`, `_core_features`, `_advanced`, and `_reference`. Preview with `docs/bin/serve.sh`.
- Voice: Rails guides. Second person, present tense, show the code before explaining it, motivate each feature with the problem it solves in one sentence. No em dashes, no hype, no "simply".
- Lead with short, working public API examples. Show how features combine when it helps the reader build something. Keep the title, description, and "After reading this guide" opening; introduce concepts before adding a summary table.
- Front-matter `description` becomes the page's llms.txt entry and social card text: one compelling sentence, no `&`, `<`, or `>`.
- Cross-link with `{% link _collection/page.md %}`, never hard-coded URLs.
- `docs/_reference/available-models.md` is generated; never edit it.

## Before opening the PR

1. `overcommit --run` passes.
2. New behavior has specs; changed provider behavior has re-recorded cassettes, reviewed for secrets.
3. Public API changes are documented in `docs/` and have RDoc.
4. The PR does one thing, references its approved issue, and explains the problem before the solution.

Tinjau sumber

Harga dan biaya penggunaan

Dapatkan skill: Harga belum dikonfirmasi
Jalankan: Persyaratan belum dikonfirmasi. Periksa biaya agen, API, dan layanan di sumbernya.
Lisensi: MIT
Harga belum dikonfirmasi: Harga belum dikonfirmasi. Tautan sumber dan instalasi yang ada tetap tersedia.

Gratis diperoleh bukan berarti gratis dijalankan. Harga bukan penilaian keamanan. Kirim informasi harga →

Sumber skill tercatat

Jalur instruksi telah dicatat. Ini bukan uji eksekusi, jaminan keamanan, atau sertifikasi kompatibilitas.

Tinjau sebelum memasang: Hindari pemasangan otomatis

Lisensi: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
Persetujuan tinjauan AI belum ada
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Buka audit lengkap

Daftar alat adalah petunjuk metadata, bukan kompatibilitas teruji. Prompt adalah saran.

Mulai dengan tugas kecil

1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.

Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.

Sumber dan catatan penggunaan

TerindeksDiperiksa statis

Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.

Repositori sumber: crmne/ruby_llm
Lisensi: MIT
Versi: Unknown
Push GitHub terakhir: 14 Sep 2026
Direktori diperbarui: 15 Sep 2026
Jalur instruksi: .claude/skills/contributing/SKILL.md @ 08d273f1f011

Versi dilaporkan dalam metadata direktori; periksa rilis sumber.

Kualitas

78/100

Kuat

Kepercayaan

67/100

Hanya sandbox

Audit

80/100

Perlu ditinjau

Buka audit lengkap Lihat laporan evaluasi

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
Persetujuan tinjauan AI belum ada
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
Hasil: —

Menyalin bukan memasang. Jumlah instalasi memerlukan laporan berhasil dan bukan jaminan kualitas menyeluruh.

Akses agent

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka API pemasangan Format teks LLM Buka Manifest Rencana resolusi otomatis

Detail lainnya

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    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Financial research output is not financial advice; require human review before any live investment decision",
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 78,
    "label": "Strong"
  },
  "supply": {
    "track": "Research and knowledge work",
    "scenario": "Research agents",
    "maintenance": "26d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "high-compliance environments without internal security review",
    "No major risk signals from current metadata",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "AI review approval is missing"
  ],
  "agent_contract": {
    "task_input": "Use contributing in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 75/100 Strong shortlist",
      "Audit: 80/100 Needs review",
      "Safety: 36/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "crmne-contributing (contributing)",
      "install_command": "npx skills add crmne/ruby_llm --skill contributing",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "crmne-contributing",
      "task": "Use contributing in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/crmne-contributing",
    "api": "https://www.openagentskill.com/api/agent/skills/crmne-contributing",
    "audit": "https://www.openagentskill.com/skills/crmne-contributing/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=crmne-contributing&task=Use%20contributing%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20contributing%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20contributing%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/crmne-contributing/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/crmne-contributing"
  }
}

Untuk kreator

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator: crmne
Sumber: crmne/ruby_llm
Diindeks oleh: Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan crmne, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit berbagi

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/crmne-contributing?metric=listed&label=Listed)](https://www.openagentskill.com/skills/crmne-contributing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/crmne-contributing?metric=trust&label=Trust)](https://www.openagentskill.com/skills/crmne-contributing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/crmne-contributing?metric=audit&label=Audit)](https://www.openagentskill.com/skills/crmne-contributing/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/crmne-contributing?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/crmne-contributing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

Pratinjau badge Buka audit Kit kreator

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.