# Round-trip verification results Real-CLI verification performed at branch-cut. Each harness's actual tool was used to load the generated artifacts and report what it found. > Reproduce locally: see the recipes at the bottom of this file. ## Summary | Harness | CLI version | Result | Artifacts loaded | Notes | |---|---|---|---|---| | **OpenCode** | 1.1.23 | ✅ pass | 191 / 191 subagents discovered | All emitted agents pass OpenCode's parser. 2 OpenCode built-ins (`explore`, `general`) appear alongside ours. | | **Gemini CLI** | 0.42.0 | ✅ pass | `gemini extensions validate .` returns "successfully validated" | Native skills + subagents at extension root recognized. | | **Codex CLI** | 0.133.0 | ✅ pass (structural) | All 191 agent TOMLs parse via Python `tomllib`; AGENTS.md within budget (43 lines / 500 tokens) | Codex doctor surfaces no errors; deeper "did the model actually load the skill" requires interactive verification. | | **Cursor** | (editor-only) | n/a | n/a | No CLI; manual verification recipe below. | | **Copilot** | (structural) | ✅ pass | 191 agent profiles, 155 skills, 25 commands all validated | No CLI round-trip tool yet; structural validation via `make validate` passes. | ## Issues surfaced and fixed during round-trip The real-CLI runs caught two bugs that pure unit tests missed. Both are now fixed and covered by regression tests: 1. **YAML block-scalar descriptions** (`description: >` followed by indented lines). `tools/adapters/base.py:parse_frontmatter` was producing strings starting with the literal `>` indicator, which then broke OpenCode's agent loader. Fix: detect `>`, `>-`, `|`, `|-` and collapse the following indented lines into a single string. Affected agents: 4 (arm-cortex-expert + 3 meigen-ai-design agents). 2. **OpenCode permission block degraded to deny-everything** when source `tools:` only contained MCP tools (`mcp__...`) or was an empty list `[]`. The OpenCode adapter emitted `read: deny, edit: deny, ...` which made the agent inert. Fix: if no source tool maps to a known OpenCode permission key, omit the permission block entirely (default permissive — MCP tools come in via the MCP server config, not the permission allowlist). 3. **OpenCode rejected `$source` extension key in `opencode.json`.** Schema only allows `$schema`. Fix: drop the custom `$source` annotation. The adapter emits a clean `{"$schema": "https://opencode.ai/config.json"}` now. ## Reproduce locally ### OpenCode round-trip ```bash # 1. Generate artifacts make generate HARNESS=opencode # 2. Copy into a scratch directory (or use the repo root directly) mkdir -p /tmp/round-trip && cd /tmp/round-trip cp -r /path/to/claude-agents/.opencode . cp /path/to/claude-agents/opencode.json . # 3. Verify opencode agent list | grep "subagent)$" | wc -l # Expected: 191 source agents discovered (plus OpenCode built-ins: explore, general) ``` ### Gemini round-trip ```bash # Native validator gemini extensions validate /path/to/claude-agents # Or link as an extension and probe gemini extensions link /path/to/claude-agents gemini skills list # should list all generated skills gemini extensions list | grep claude-code-workflows ``` ### Codex round-trip ```bash # Generate AGENTS.md + .codex/skills/ + .codex/agents/ make generate HARNESS=codex # Symlink into ~/.codex (Codex uses CODEX_HOME) mkdir -p ~/.codex/skills ~/.codex/agents ln -sf /path/to/claude-agents/.codex/skills/* ~/.codex/skills/ ln -sf /path/to/claude-agents/.codex/agents/* ~/.codex/agents/ # AGENTS.md is read automatically when codex runs from the repo root codex doctor | head -40 # no warnings expected from our artifacts # Deeper: launch interactive session and ask Codex to use a generated skill by name. # Requires interactive use — not automatable without consuming API tokens. codex > /skills # browser should list all generated skills > have backend-development__backend-architect summarize plugins/backend-development ``` ### Cursor (no CLI) ```bash # Generate make generate HARNESS=cursor # Manually: # 1. Open Cursor 2.5+ # 2. Settings → Plugins → Add Local Plugin Source # 3. Point at /path/to/claude-agents/ # 4. Verify the marketplace browser lists all 81 local plugins # 5. Verify .cursor/rules/*.mdc files activate per their `globs` # 6. Skills under .claude/skills/ should auto-trigger from descriptions ``` ### Copilot (no CLI round-trip yet) ```bash # Generate make generate HARNESS=copilot # Structural validation (parses every generated artifact) make validate # Verify artifact tree ls .copilot/agents/ # 191 agent profiles (*.agent.md) ls .copilot/skills/ # 155 skill dirs (each with SKILL.md) ls .copilot/commands/ # command-prompt files # Global install (optional) make install-copilot # symlinks .copilot/ -> ~/.copilot/ ``` Copilot currently lacks a CLI verification tool. Manual testing: open VS Code, open the Copilot Chat (Ctrl+Shift+I), and verify agents appear in the agent selector and skills auto-trigger from matching prompts. ## Automated structural checks (no CLI needed) The `tools/validate_generated.py` script approximates round-trip without installing the harnesses: ```bash make validate # all five harnesses make validate HARNESS=codex # one only ``` It parses every TOML/JSON/MDC artifact against documented schemas. Run before merging any adapter change. ## Recurring drift detection ```bash make garden # find stale artifacts, oversized context files, dead links, etc. ``` `tools/doc_gardener.py` per the OpenAI harness-engineering pattern — recurring task that surfaces drift with concrete remediation hints. ## Coverage limits The pure-structural validators do **not** verify that the model can actually consume the artifacts at runtime. Specifically untested by the automated suite: - Whether Codex's skill discovery actually selects our skills on relevant prompts (vs. ignoring them or selecting wrong ones). - Whether OpenCode's `task` tool dispatches our subagents end-to-end. - Whether Cursor 2.5+ marketplace browser displays our plugin entries (requires the editor; can't be scripted). - Whether Gemini's `@` invocation runs our generated subagent against a real prompt. - Whether Copilot's agent profile and skill discovery actually loads our artifacts end-to-end (no CLI; requires VS Code editor). These require interactive use and API-token-burning runs. The recipes above show how to perform them manually.