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

5.3 KiB

claude-agents — multi-harness agentic plugin marketplace

Production-ready agentic-workflow building blocks: 94 plugins (90 local + 4 external), 203 agents, 175 skills, 109 commands. Native source-of-truth for Claude Code; also consumed by OpenAI Codex CLI, Cursor, OpenCode, and Gemini CLI from a single Markdown source.

This file is the canonical context file. Codex / Cursor / OpenCode read it directly. Claude Code reads it via CLAUDE.md, a symlink to this file. Gemini CLI reads it via gemini-extension.json (contextFileName) / .gemini/settings.json.

Read this file like a table of contents. Detail lives in docs/. Authoring conventions live in docs/authoring.md. Per-harness setup and capability deltas live in docs/harnesses.md. Gemini-specific setup is in GEMINI.md (also auto-loaded by Gemini CLI). This file should never grow beyond ~150 lines (per OpenAI's harness-engineering practice).

Map

Working in this repo

  • Python tooling: uv (package manager), ruff (lint/format), ty (type check). Do not use pip / mypy / black.
  • Plugins live under plugins/<name>/ with auto-discovery — see docs/authoring.md for frontmatter shapes.
  • Plugin names: lowercase, hyphen-separated. Never use __ (it's the adapter namespace separator).
  • Never commit secrets. Never run destructive git (force-push, reset --hard, branch -D) without explicit ask.

Quality gates (run these before pushing)

make validate STRICT=1     # structural validation across all harness outputs
make garden                # drift detection (dead links, stale artifacts, oversize skills)
make test                  # full pytest suite (plugin-eval + tools/tests/)
make smoke-test            # real-CLI subprocess tests against generated artifacts

CI (.github/workflows/validate.yml) runs all four on every PR plus installs OpenCode + Gemini CLI for live verification.

Regenerating per-harness artifacts

make generate HARNESS=codex      # .codex/skills, .codex/agents, .codex/plugins/<p>/, .agents/plugins/marketplace.json
make generate HARNESS=cursor     # .cursor-plugin/{marketplace,plugin}.json, .cursor/rules/
make generate HARNESS=opencode   # .opencode/{skills,agents,commands,plugins}/, opencode.json
make generate HARNESS=gemini     # skills/, agents/, commands/ at extension root
make generate-all                # all four

Generated artifacts are committed so each harness installs natively from a clone / GitHub URL (native-install commands in docs/harnesses.md). Run make generate-all before committing source changes — CI fails on drift. Source-of-truth lives only under plugins/; never hand-edit generated files.

Skills (cross-harness)

175 skills under plugins/*/skills/<n>/SKILL.md — discoverable by every harness:

  • Claude Code: auto-discovery via Anthropic's SKILL.md spec
  • Codex CLI: mirrored to .codex/skills/<plugin>__<skill>/ (8 KB body cap; detail in references/details.md)
  • OpenCode: mirrored to .opencode/skills/<plugin>-<skill>/ using hyphenated names for global install
  • Cursor: reads .claude/skills/ directly (no re-emit)
  • Gemini CLI: native skills at skills/<plugin>__<skill>/SKILL.md

Top-level skills/ is Gemini output; do not use it for OpenCode installs.

Subagents (cross-harness)

203 subagents under plugins/*/agents/<name>.md. Per-harness transpilation:

  • Codex: .codex/agents/<plugin>__<agent>.toml (drop tools:, map model alias to the GPT-5.x family, infer sandbox_mode)
  • OpenCode: .opencode/agents/<plugin>__<agent>.md with mode: subagent + permission: block (locked agents — those with source tools: [] — get deny-everything except base skill/task)
  • Gemini: agents/<plugin>__<agent>.md (April 2026 subagent spec)
  • Cursor: reads .claude/agents/ directly

Why this file is short

Per OpenAI's harness-engineering practice: this file is a map, not an encyclopedia. Procedural detail lives in skills (loaded on demand by agents). Reference material lives in docs/ (loaded when an agent navigates). A single bloated AGENTS.md crowds out the task, rots quickly, and is hard to verify mechanically. Keep it lean; push detail elsewhere.