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Seth Hobson be57c0b2e3 feat: multi-harness plugin marketplace (Codex, Cursor, OpenCode, Gemini) (#541)
* feat(adapters): multi-harness framework + harness_portability eval dimension

Turn this Claude Code plugin marketplace into a generic agentic-harness
marketplace. Adapters under tools/adapters/ emit harness-native artifacts
for OpenAI Codex CLI, Cursor, OpenCode, and Gemini CLI from a single
Markdown source. Source-of-truth stays under plugins/ — Claude Code is
unchanged.

Framework (tools/adapters/):
- base.py — PluginSource parser, HarnessAdapter ABC, write/mirror helpers
  (path-traversal guard, UTF-8-safe), inline-list + block-list + block-scalar
  YAML-ish parser, _utf8_safe_cut, _split_inline_list, _normalize_author
- capabilities.py — per-harness capability matrix, TOOL_NAME_MAPS,
  MODEL_ALIASES, resolve_model() with explicit warnings
- codex.py — emits .codex/{skills,agents}/ + AGENTS.md (≤150-line
  table-of-contents). Fence-aware body splitter, _utf8_safe_cut for
  multibyte safety, _yaml_scalar with reserved-word + special-char quoting.
  Skill/command name collision detection (and second-order __cmd fallback).
- cursor.py — emits .cursor-plugin/{plugin,marketplace}.json + curated
  .cursor/rules/*.mdc. _validate_mdc_frontmatter handles YAML block scalars
  (no false positives on colons in description body). _normalize_author
  handles dict, npm-style strings, and author lists.
- opencode.py — transpiles agents to .opencode/agents/<id>.md with
  mode:subagent + permission: deny-everything-else block (skill/task always
  allowed as base capabilities — Claude's implicit defaults).
- gemini.py — emits native skills/, agents/, and commands/ at extension
  root (April 2026 spec). Tool-allowlist remapped via TOOL_NAME_MAPS.

CLI + tooling:
- tools/generate.py — unified `make generate HARNESS=<x> [PLUGIN=<y>]`,
  with --clean (containment-guarded; case-insensitive on Darwin/Win32),
  --prune (orphan removal across all per-harness output trees), --strict
  (warnings fail), per-plugin error aggregation, refuses --clean --plugin
  (would silently wipe other plugins' artifacts).
- tools/validate_generated.py — structural validation across all four
  harness outputs. Codex 8KB cap → error. _extract_permission_block
  correctly handles nested permission keys (column-0 only).
- tools/doc_gardener.py — recurring drift detection per OpenAI harness-
  engineering principle. STALE_ARTIFACT (info), DEAD_LINK (error),
  MARKETPLACE_ORPHAN (error), SKILL_OVER_CODEX_CAP (warning), grouped
  output sorted by severity.

plugin-eval (extends existing framework):
- New harness_portability dimension (6% weight, rebalanced from existing
  static sub-scores). Surfaces non-portable patterns with concrete
  remediation hints: SKILL_OVER_CODEX_CAP, CLAUDE_TOOL_REFS,
  CLAUDE_TOOL_PROSE, AGENT_NAME_COLLISION, BARE_MODEL_ALIAS.
- _CAMEL_TOOL_PATTERN requires Claude-tool context (no false positives
  on Rust's `Task` etc.). _TOOL_PROSE_PATTERN case-sensitive on tool
  names, case-insensitive on the leading article.
- Findings do NOT also feed anti_pattern_penalty (no double-counting).

Documentation:
- Top-level guides: CODEX.md, CURSOR.md, OPENCODE.md (≤150 lines each,
  table-of-contents pattern per OpenAI harness-engineering post)
- docs/harnesses.md — capability matrix, graceful-degradation table,
  generated output paths
- docs/authoring.md — portable-content style guide (tools, models,
  collision rules, fence-respect)
- docs/round-trip-results.md — real-CLI verification recipes (OpenCode
  discovers 193 subagents, Gemini extensions validate passes, Codex
  TOMLs all parse)
- CONTRIBUTING.md — new file pointing at docs/authoring.md
- README.md — rewritten for multi-harness (145 lines, was 460)
- CLAUDE.md — trimmed to 60-line table-of-contents
- GEMINI.md — trimmed from 1500 to 500 tokens (3× over budget previously)

Tests: 181 passing (103 plugin-eval + 78 tools/tests). Real-CLI round-trip
verified for OpenCode, Gemini, and Codex (TOML parses).

Replaces tools/generate_gemini_commands.py with the unified CLI.

* refactor(skills): extract detail to references/details.md (~75 skills)

Apply Anthropic's canonical SKILL.md progressive-disclosure pattern across
the marketplace: SKILL.md body becomes a navigation tier (trigger phrasing
+ quick start), detailed templates and worked examples move to
references/details.md (loaded on demand by the agent).

Motivation: OpenAI Codex CLI hard-truncates skills at 8 KB. Before this
change, ~90 skills exceeded that cap and would silently break on Codex.
The progressive-disclosure pattern is also Anthropic's documented
recommendation for token efficiency — Claude Code reads references/ files
on demand when the body navigation says to.

What's extracted, by pattern:
- Pass 1 (## Templates section): 19 skills — full template libraries
  moved to references/details.md
- Pass 2 (## Implementation Patterns / ## Advanced Patterns): 13 skills
- Pass 3 (everything between nav-tier and wrap-tier headings): 53 skills
- Conservative re-extraction for 8 skills that got over-reduced — kept
  ~6-7 KB inline (most of the quick-start tier) plus references/ overflow

What stays inline (SKILL.md navigation tier):
- description: frontmatter (triggering — unchanged for all skills)
- ## When to Use This Skill / ## Core Concepts / ## Quick Start
- ## Best Practices / ## Troubleshooting / ## See Also wrap-ups
- A pointer note ("see references/details.md") so the agent knows where
  to look for detail

What goes to references/details.md (detail tier, on-demand load):
- ## Templates (full code template libraries)
- ## Implementation Patterns / ## Advanced Patterns (deep examples)
- Mid-skill walkthroughs that exceed the inline budget

Also in this commit:
- plugins/brand-landingpage description trimmed from 958→543 chars
  (preserves trigger phrasing, drops verbose example-quote list)

Net effect:
- SKILL_OVER_CODEX_CAP findings: 90 → 10 (88% reduction)
- All triggers unchanged — discovery behavior identical across harnesses
- 75 new references/details.md files with the extracted content
- Same depth of guidance, loaded progressively

Remaining 10 oversized skills are complex multi-section docs (e.g.
postgresql, code-review-excellence, evaluation-methodology) that need
per-skill manual judgment — flagged by `make garden` for future work.

* chore: bump all plugin versions (multi-harness release)

Patch-bump every local plugin (81) in both .claude-plugin/marketplace.json
entries and each plugins/<name>/.claude-plugin/plugin.json. Minor-bump the
top-level marketplace metadata.version (1.6.0 → 1.7.0) to signal the
multi-harness adapter framework addition.

The external git-subdir entry (qa-orchestra) is unaffected — its version
is governed by its upstream repo.

* fix(opencode): preserve explicit tools:[] + word-boundary subtask match

Addresses two Codex review findings on PR #541.

## P1 — `tools: []` silently upgraded to permissive (privilege escalation)

Before: `_build_permission_block` returned `{}` for any empty list, which
omits the `permission:` block entirely from the emitted agent. An author
who explicitly wrote `tools: []` to lock down an advisory-only agent got
an UNRESTRICTED agent in OpenCode. Affected agent in this tree:
`plugins/arm-cortex-microcontrollers/agents/arm-cortex-expert.md`.

Fix: `_build_permission_block` now takes a `has_tools_field` flag so the
caller can distinguish "tools: key missing" (Claude default permissive)
from "tools: []" (explicit lock-down). The lock-down case emits a
deny-everything block that allows ONLY the base capabilities (skill, task)
that Claude Code always grants implicitly. Verified against the real
arm-cortex-expert agent — now emits read/edit/write/bash/grep/glob/list:
deny, task/skill: allow.

## P2 — `"agent" in cmd.body.lower()` false-positives on substrings

Before: a command body containing `PerformanceReviewAgent` (class name
in a code snippet) or `useragent` triggered `subtask: true`, changing
runtime behavior based on incidental text.

Fix: switch to a compiled word-boundary regex `\b(agent|subagent)s?\b`
(case-insensitive). Tests confirm the substring `PerformanceReviewAgent`
no longer fires, while a real "spawn a subagent" sentence still does.

## Tests

3 new regression tests in tools/tests/test_adapters.py:
- `test_explicit_empty_tools_yields_locked_permission_block` (P1)
- `test_missing_tools_field_yields_no_permission_block` (P1 boundary)
- `test_subtask_inference_word_boundary` (P2)

184 total tests pass (was 181). OpenCode round-trip still discovers all
193 subagents; arm-cortex-expert agent is now properly locked down.

* test: behavioral verification + CI gates for multi-harness pipeline

Adds three layers of automated verification that pure-Python parser tests
miss, plus the CI jobs that turn them into hard gates. Catches the kinds
of issues that previously only surfaced when a real user installed the
marketplace and tried to use it.

## test_real_world.py — real-source structural tests

Runs against the actual `plugins/` tree (not synthetic fixtures). Catches
issues that only appear on real content:

- every marketplace entry resolves to a plugins/<name>/ dir
- every local plugin dir appears in marketplace.json
- marketplace.json version == per-plugin plugin.json version (catches drift)
- every plugin loads via load_plugin() without error
- no plugin name contains `__` (adapter namespace separator)
- every agent has name + description; every skill has a trigger phrase
  (same regex plugin_eval's MISSING_TRIGGER check uses)
- no agent name collides with Codex built-ins
- every refactored skill (with `references/details.md`) has:
  - meaningful detail content (>=500 B in details.md)
  - a pointer to references/ in the SKILL.md body
  - a navigation-tier heading preserved (When to Use, Overview, etc.)
  - body >= 600 B (not a stub)
- every plugin.json has name + version matching the dir

This test pass found and fixed three real defects before commit:
- ship-mate/skills/scan: description had no trigger phrase ("Use when…")
- reverse-engineering/skills/memory-forensics: nav-tier section lost
  during extraction
- reverse-engineering/skills/binary-analysis-patterns: same

All three are now fixed (preserved trigger phrasing, added When-to-Use
sections back to the skills my extraction over-trimmed).

## test_round_trip.py — generate→parse→verify

CI runs this AFTER `make generate-all`. Catches generation-time regressions:

- OpenCode/Codex/Gemini agent counts match source agent count (no skips)
- every Codex SKILL.md under 8 KB (the cap that would silently truncate)
- every Codex agent TOML has required fields + valid sandbox_mode
- every OpenCode agent has mode in {primary,subagent,all} and
  provider-prefixed model
- locked agents (source `tools: []`) emit proper deny-everything permission
  block with skill/task allow (regression guard for PR-541 P1)
- every Gemini @{path} injection resolves to a real source file
- every Gemini command TOML has prompt + {{args}} placeholder
- every context file (CLAUDE.md, AGENTS.md, GEMINI.md, etc.) within
  150-line cap
- Cursor marketplace + per-plugin manifests cover all local plugins
- .cursor/rules/*.mdc only use the 3 documented frontmatter keys

## test_cli_smoke.py — real-CLI subprocess tests

Invokes the actual harness binaries (OpenCode, Gemini, Codex, Claude Code)
against the generated artifacts. Catches CLI-level issues pure-Python
parsing can't see: schema-loader drift, plugin-discovery bugs, version
incompatibilities.

- `opencode agent list` — must succeed AND discover every source agent
  (currently 191 + 2 OpenCode built-ins)
- `gemini extensions validate <repo>` — must return success
- `codex doctor` — must report healthy install
- every Codex agent TOML must parse with stdlib `tomllib`
- `claude --version` — sanity check the Claude Code CLI loads
- marketplace.json must have owner + metadata.version for Claude Code's loader

Per-CLI tests skip gracefully when the binary isn't on PATH, so local
devs only exercise what they have installed. CI installs OpenCode +
Gemini and turns those skips into hard gates.

## Makefile + CI

- `make test` — full pytest suite (plugin-eval + tools/tests/)
- `make smoke-test` — generates if needed, then runs real-CLI smoke tests
- `.github/workflows/validate.yml` extended with:
  - `tools-tests` job — runs pytest tools/tests/
  - `multi-harness-generate` job — `make generate-all && make validate
    STRICT=1 && make garden`, uploads generated artifacts on every run
  - `cli-smoke-test` job — installs OpenCode + Gemini, runs test_cli_smoke.py

## Test counts

- Before: 184 tests
- After: 386 tests (parameterized real-source tests over all 82 plugins)
- All passing locally on OpenCode 1.15.7 + Gemini 0.42.0 + Codex 0.133.0
  + Claude Code 2.1.148
2026-05-22 08:18:21 -04:00

9.8 KiB

context-driven-development — detailed patterns and worked examples

Core Philosophy

Context-Driven Development treats project context as a first-class artifact managed alongside code. Instead of relying on ad-hoc prompts or scattered documentation, establish a persistent, structured foundation that informs all AI interactions.

Key principles:

  1. Context precedes code: Define what you're building and how before implementation
  2. Living documentation: Context artifacts evolve with the project
  3. Single source of truth: One canonical location for each type of information
  4. AI alignment: Consistent context produces consistent AI behavior

The Workflow

Follow the Context → Spec & Plan → Implement workflow:

  1. Context Phase: Establish or verify project context artifacts exist and are current
  2. Specification Phase: Define requirements and acceptance criteria for work units
  3. Planning Phase: Break specifications into phased, actionable tasks
  4. Implementation Phase: Execute tasks following established workflow patterns

Artifact Relationships

product.md - Defines WHAT and WHY

Purpose: Captures product vision, goals, target users, and business context.

Contents:

  • Product name and one-line description
  • Problem statement and solution approach
  • Target user personas
  • Core features and capabilities
  • Success metrics and KPIs
  • Product roadmap (high-level)

Update when:

  • Product vision or goals change
  • New major features are planned
  • Target audience shifts
  • Business priorities evolve

product-guidelines.md - Defines HOW to Communicate

Purpose: Establishes brand voice, messaging standards, and communication patterns.

Contents:

  • Brand voice and tone guidelines
  • Terminology and glossary
  • Error message conventions
  • User-facing copy standards
  • Documentation style

Update when:

  • Brand guidelines change
  • New terminology is introduced
  • Communication patterns need refinement

tech-stack.md - Defines WITH WHAT

Purpose: Documents technology choices, dependencies, and architectural decisions.

Contents:

  • Primary languages and frameworks
  • Key dependencies with versions
  • Infrastructure and deployment targets
  • Development tools and environment
  • Testing frameworks
  • Code quality tools

Update when:

  • Adding new dependencies
  • Upgrading major versions
  • Changing infrastructure
  • Adopting new tools or patterns

workflow.md - Defines HOW to Work

Purpose: Establishes development practices, quality gates, and team workflows.

Contents:

  • Development methodology (TDD, etc.)
  • Git workflow and commit conventions
  • Code review requirements
  • Testing requirements and coverage targets
  • Quality assurance gates
  • Deployment procedures

Update when:

  • Team practices evolve
  • Quality standards change
  • New workflow patterns are adopted

tracks.md - Tracks WHAT'S HAPPENING

Purpose: Registry of all work units with status and metadata.

Contents:

  • Active tracks with current status
  • Completed tracks with completion dates
  • Track metadata (type, priority, assignee)
  • Links to individual track directories

Update when:

  • New tracks are created
  • Track status changes
  • Tracks are completed or archived

See references/artifact-templates.md for copy-paste starter templates.

Context Maintenance Principles

Keep Artifacts Synchronized

Ensure changes in one artifact reflect in related documents:

  • New feature in product.md → Update tech-stack.md if new dependencies needed
  • Completed track → Update product.md to reflect new capabilities
  • Workflow change → Update all affected track plans

Update tech-stack.md When Adding Dependencies

Before adding any new dependency:

  1. Check if existing dependencies solve the need
  2. Document the rationale for new dependencies
  3. Add version constraints
  4. Note any configuration requirements

Update product.md When Features Complete

After completing a feature track:

  1. Move feature from "planned" to "implemented" in product.md
  2. Update any affected success metrics
  3. Document any scope changes from original plan

Verify Context Before Implementation

Before starting any track:

  1. Read all context artifacts
  2. Flag any outdated information
  3. Propose updates before proceeding
  4. Confirm context accuracy with stakeholders

Greenfield vs Brownfield Handling

Greenfield Projects (New)

For new projects:

  1. Run /conductor:setup to create all artifacts interactively
  2. Answer questions about product vision, tech preferences, and workflow
  3. Generate initial style guides for chosen languages
  4. Create empty tracks registry

Characteristics:

  • Full control over context structure
  • Define standards before code exists
  • Establish patterns early

Brownfield Projects (Existing)

For existing codebases:

  1. Run /conductor:setup with existing codebase detection
  2. System analyzes existing code, configs, and documentation
  3. Pre-populate artifacts based on discovered patterns
  4. Review and refine generated context

Characteristics:

  • Extract implicit context from existing code
  • Reconcile existing patterns with desired patterns
  • Document technical debt and modernization plans
  • Preserve working patterns while establishing standards

Benefits

Team Alignment

  • New team members onboard faster with explicit context
  • Consistent terminology and conventions across the team
  • Shared understanding of product goals and technical decisions

AI Consistency

  • AI assistants produce aligned outputs across sessions
  • Reduced need to re-explain context in each interaction
  • Predictable behavior based on documented standards

Institutional Memory

  • Decisions and rationale are preserved
  • Context survives team changes
  • Historical context informs future decisions

Quality Assurance

  • Standards are explicit and verifiable
  • Deviations from context are detectable
  • Quality gates are documented and enforceable

Directory Structure

conductor/
├── index.md              # Navigation hub linking all artifacts
├── product.md            # Product vision and goals
├── product-guidelines.md # Communication standards
├── tech-stack.md         # Technology preferences
├── workflow.md           # Development practices
├── tracks.md             # Work unit registry
├── setup_state.json      # Resumable setup state
├── code_styleguides/     # Language-specific conventions
│   ├── python.md
│   ├── typescript.md
│   └── ...
└── tracks/
    └── <track-id>/
        ├── spec.md
        ├── plan.md
        ├── metadata.json
        └── index.md

Context Lifecycle

  1. Creation: Initial setup via /conductor:setup
  2. Validation: Verify before each track
  3. Evolution: Update as project grows
  4. Synchronization: Keep artifacts aligned
  5. Archival: Document historical decisions

Context Validation Checklist

Before starting implementation on any track, validate context:

Product Context

  • product.md reflects current product vision
  • Target users are accurately described
  • Feature list is up to date
  • Success metrics are defined

Technical Context

  • tech-stack.md lists all current dependencies
  • Version numbers are accurate
  • Infrastructure targets are correct
  • Development tools are documented

Workflow Context

  • workflow.md describes current practices
  • Quality gates are defined
  • Coverage targets are specified
  • Commit conventions are documented

Track Context

  • tracks.md shows all active work
  • No stale or abandoned tracks
  • Dependencies between tracks are noted

Common Anti-Patterns

Avoid these context management mistakes:

Stale Context

Problem: Context documents become outdated and misleading. Solution: Update context as part of each track's completion process.

Context Sprawl

Problem: Information scattered across multiple locations. Solution: Use the defined artifact structure; resist creating new document types.

Implicit Context

Problem: Relying on knowledge not captured in artifacts. Solution: If you reference something repeatedly, add it to the appropriate artifact.

Context Hoarding

Problem: One person maintains context without team input. Solution: Review context artifacts in pull requests; make updates collaborative.

Over-Specification

Problem: Context becomes so detailed it's impossible to maintain. Solution: Keep artifacts focused on decisions that affect AI behavior and team alignment.

Integration with Development Tools

IDE Integration

Configure your IDE to display context files prominently:

  • Pin conductor/product.md for quick reference
  • Add tech-stack.md to project notes
  • Create snippets for common patterns from style guides

Git Hooks

Consider pre-commit hooks that:

  • Warn when dependencies change without tech-stack.md update
  • Remind to update product.md when feature branches merge
  • Validate context artifact syntax

CI/CD Integration

Include context validation in pipelines:

  • Check tech-stack.md matches actual dependencies
  • Verify links in context documents resolve
  • Ensure tracks.md status matches git branch state

Session Continuity

Conductor supports multi-session development through context persistence:

Starting a New Session

  1. Read index.md to orient yourself
  2. Check tracks.md for active work
  3. Review relevant track's plan.md for current task
  4. Verify context artifacts are current

Ending a Session

  1. Update plan.md with current progress
  2. Note any blockers or decisions made
  3. Commit in-progress work with clear status
  4. Update tracks.md if status changed

Handling Interruptions

If interrupted mid-task:

  1. Mark task as [~] with note about stopping point
  2. Commit work-in-progress to feature branch
  3. Document any uncommitted decisions in plan.md