项目文件夹

文件
Seth Hobson baa5bd7997 feat: add llm-finetuning and dgx-spark-ops plugins (eval-gated fine-tuning lifecycle) (#624)
* feat(dgx-spark-ops): scaffold plugin and register in marketplace

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(dgx-spark-ops): add spark-environment-setup skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(dgx-spark-ops): tighten spark-environment-setup per review

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(dgx-spark-ops): add spark-training-gotchas skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(dgx-spark-ops): align preflight.sh output contract with docs

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(dgx-spark-ops): add spark-memory-thermal-ops skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(dgx-spark-ops): trim spark-memory-thermal-ops and source 68GB anchor

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(dgx-spark-ops): add dgx-spark-ops-engineer agent

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(dgx-spark-ops): defer agent facts to skills

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(dgx-spark-ops): add /spark-preflight command

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): scaffold plugin and register in marketplace

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add finetuning-method-selection skill with dated model catalog

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add lora-qlora-recipes skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add preference-optimization skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add grpo-rlvr-training skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(llm-finetuning): add isolation warning to execution reward

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add vision-sft skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add dataset-curation skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(llm-finetuning): correct loss-masking example in dataset-curation

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add eval-harness-first skill (Phase 0 gate)

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(llm-finetuning): bring eval-harness-first into line band

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(llm-finetuning): reclaim byte headroom in eval-harness-first

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add trace-to-training-data skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add checkpoint-promotion skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add quantized-export skill

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add llm-finetuning-architect agent

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add llm-finetuning-training-engineer agent

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add llm-finetuning-eval-engineer agent

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add /finetune phase-gated lifecycle command

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(llm-finetuning): thread checkpoint path into /finetune Phase 6

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* feat(llm-finetuning): add /promote-checkpoint command

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(llm-finetuning): thread checkpoint path via phase5.output in /promote-checkpoint

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix(llm-finetuning): robust checkpoint discovery and goldens fingerprint in re-gate

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* docs: register llm-finetuning and dgx-spark-ops (94 plugins, 203 agents, 175 skills, 109 commands)

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* docs(agents): add fine-tuning and spark-ops agent entries (203 agents)

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* chore: generate per-harness artifacts for llm-finetuning and dgx-spark-ops

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix: final-review cleanups for fine-tuning plugins

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix: address PR #624 review feedback (G1 NGC detection, Phase 3 fallback dispatch, registry metadata)

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix: enforce sandbox boundary in execution grader and reward examples

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix: address CodeRabbit review findings on PR #624

Verified and fixed 37 of 43 outstanding CodeRabbit findings across the
llm-finetuning and dgx-spark-ops plugins (skipping 6 confirmed false
positives/already-fixed, with reasons in the disposition report).

Highlights: cross-file contracts (goldens fingerprint persistence,
paired-arena stage numbering, canonical golden-ID field, RERUN
resolution before promotion) now match between finetune.md,
promote-checkpoint.md, and checkpoint-promotion's templates. TRL API
usages (SFTConfig.max_length, trl.experimental ORPO/CPO imports)
verified against live TRL docs rather than blindly renamed. Several
runnable examples hardened against real failure modes: malformed
judge output, empty arena results, non-distinct DPO pairs, unbounded
rejection-sampling fan-out, non-deterministic smoke-test comparisons,
silent FP8-to-bf16 fallback, and orphaned background thermal-sampler
processes. Container detection (G9) and LoRA adapter-size math fixed
in both dgx-spark-ops and llm-finetuning where the same bugs were
independently present in each plugin.

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix: apply dogfood friction-log remediations (F1-F32) from DGX Spark run

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf

* fix: address CodeRabbit round-2 findings (digest pins, suite-size math, monkeypatch scoping)

Claude-Session: https://claude.ai/code/session_01RsN3Vz5fZRTdVMkNtmxhSf
2026-07-14 13:18:02 -04:00

8.0 KiB

Agentic Plugin Marketplace

Production-ready agentic workflow building blocks: 94 plugins, 203 agents, 175 skills, 109 commands — built for Claude Code and consumed natively by OpenAI Codex CLI, Cursor, OpenCode, Gemini CLI, and GitHub Copilot from a single Markdown source.

Claude Code Codex CLI Cursor OpenCode Gemini CLI Copilot

Note

One source-of-truth (plugins/), five harnesses. Each harness gets idiomatic, harness-native artifacts — not lowest-common-denominator translations. See docs/harnesses.md for the capability matrix.

Quick start

Pick your harness:

Claude Code

/plugin marketplace add wshobson/agents
/plugin install python-development          # or any of 94 plugins

→ Full Claude Code setup, troubleshooting, and plugin catalog

Codex CLI · Cursor · OpenCode · Gemini CLI · Copilot

Codex and Cursor install natively from the committed registries (which point at the source plugins/):

npx codex-marketplace add wshobson/agents        # Codex; then install individual plugins
# Cursor: add the marketplace, then `/plugin install <name>` (reads .cursor-plugin/ + source)

Gemini and OpenCode install via clone + generate (the transformed trees are gitignored):

gh repo clone wshobson/agents ~/agents && cd ~/agents
make generate HARNESS=gemini && gemini extensions install .   # Gemini
make install-opencode                                          # OpenCode (runs generate + symlinks)

Setup details and per-harness gotchas: docs/harnesses.md. Gemini-specific setup: GEMINI.md (also auto-loaded by Gemini CLI).

What's inside

Count What it is
Plugins 94 Granular, single-purpose installable units (90 local + 4 external via git-subdir)
Agents 203 Domain experts (architecture, languages, infra, security, data, ML, docs, business, SEO)
Skills 175 Modular knowledge packages with progressive disclosure (load when activated)
Commands 109 Slash commands: scaffolding, security scans, test gen, infrastructure setup
Orchestrators 16 Multi-agent coordination workflows (full-stack, security, ML, incident response)

Browse the catalog: docs/plugins.md · docs/agents.md · docs/agent-skills.md

How it works

Each plugin is isolated and composable: agents, commands, and skills are auto-discovered from directory structure. Installing a plugin loads only its components into context — not the whole marketplace.

plugins/python-development/
├── .claude-plugin/plugin.json
├── agents/             # 3 Python agents (python-pro, django-pro, fastapi-pro)
├── commands/           # 1 scaffolding command
└── skills/             # 16 specialized skills (async, testing, packaging, …)

Tiered model strategy:

Tier Model Use
0 Fable 5 Longest-horizon autonomous work — large migrations, multi-hour runs (opt-in, premium cost)
1 Opus Architecture, security, code review, production-critical
2 inherit User-chosen — backend, frontend, AI/ML, specialized
3 Sonnet Docs, testing, debugging, API references
4 Haiku Fast operational tasks, SEO, deployment, content

→ Model configuration details

Multi-harness support

This marketplace ships to five agentic harnesses from one Markdown source. Each adapter emits harness-native artifacts (not lowest-common-denominator translations):

Harness Generates Notes
Claude Code (source-of-truth) Native marketplace.json + plugins/
Codex CLI .agents/plugins/marketplace.json + plugins/*/.codex-plugin/plugin.json (committed); .codex/skills/, .codex/agents/ (gitignored) 8 KB skill cap respected; commands → skills
Cursor .cursor-plugin/, .cursor/rules/ Thin marketplace + curated rules; reuses .claude/
OpenCode .opencode/agents/, .opencode/commands/, .opencode/skills/ permission: block from tools: allowlist; OpenCode-safe skill names
Gemini CLI skills/, agents/, commands/ (TOML) Native skills + subagents (April 2026 spec)
Copilot .copilot/agents/, .copilot/skills/, .copilot/commands/ Markdown agent profiles + SKILL.md skills + commands-as-skills; model maps to native Claude models
make generate-all                        # all five
make validate                            # structural checks
make garden                              # drift / dead-link / cap detection

Codex and Cursor install from source via committed registries; Gemini and OpenCode install via clone + make.

→ Full capability matrix and per-harness deep-dives

Quality evaluation

plugin-eval is a three-layer evaluation framework for measuring and certifying plugin/skill quality:

  • Static — deterministic structural analysis (<2s, free)
  • LLM Judge — semantic evaluation across 4 dimensions (~30s, Haiku + Sonnet)
  • Monte Carlo — statistical reliability via 50-100 simulated runs (~2-5 min)
uv run plugin-eval score path/to/skill --depth quick
uv run plugin-eval certify path/to/skill

→ PluginEval framework documentation

Documentation map

Detail lives in docs/. Read in this order:

Gemini-specific setup: GEMINI.md. All other harness setup, capability deltas, and gotchas live in docs/harnesses.md.

Contributing: CONTRIBUTING.md · Authoring: docs/authoring.md

External Memory Integration

Pensyve is included as an external git-subdir entry for Claude Code. Pensyve also maintains direct upstream integrations for this marketplace's other supported harnesses.

Harness Pensyve integration
Claude Code /plugin install pensyve from this marketplace (integrations/claude-code)
Codex CLI integrations/codex-plugin
Cursor integrations/cursor
OpenCode integrations/opencode-plugin
Gemini CLI gemini extensions install https://github.com/major7apps/pensyve
Copilot .copilot/ in repo root or ~/.copilot/ via make install-copilot

License

MIT — see LICENSE.

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