wshobson--agents
be57c0b2e3
* 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
14 KiB
14 KiB
microservices-patterns — detailed patterns and worked examples
Service Decomposition Patterns
Pattern 1: By Business Capability
# E-commerce example
# Order Service
class OrderService:
"""Handles order lifecycle."""
async def create_order(self, order_data: dict) -> Order:
order = Order.create(order_data)
# Publish event for other services
await self.event_bus.publish(
OrderCreatedEvent(
order_id=order.id,
customer_id=order.customer_id,
items=order.items,
total=order.total
)
)
return order
# Payment Service (separate service)
class PaymentService:
"""Handles payment processing."""
async def process_payment(self, payment_request: PaymentRequest) -> PaymentResult:
# Process payment
result = await self.payment_gateway.charge(
amount=payment_request.amount,
customer=payment_request.customer_id
)
if result.success:
await self.event_bus.publish(
PaymentCompletedEvent(
order_id=payment_request.order_id,
transaction_id=result.transaction_id
)
)
return result
# Inventory Service (separate service)
class InventoryService:
"""Handles inventory management."""
async def reserve_items(self, order_id: str, items: List[OrderItem]) -> ReservationResult:
# Check availability
for item in items:
available = await self.inventory_repo.get_available(item.product_id)
if available < item.quantity:
return ReservationResult(
success=False,
error=f"Insufficient inventory for {item.product_id}"
)
# Reserve items
reservation = await self.create_reservation(order_id, items)
await self.event_bus.publish(
InventoryReservedEvent(
order_id=order_id,
reservation_id=reservation.id
)
)
return ReservationResult(success=True, reservation=reservation)
Pattern 2: API Gateway
from fastapi import FastAPI, HTTPException, Depends
import httpx
from circuitbreaker import circuit
app = FastAPI()
class APIGateway:
"""Central entry point for all client requests."""
def __init__(self):
self.order_service_url = "http://order-service:8000"
self.payment_service_url = "http://payment-service:8001"
self.inventory_service_url = "http://inventory-service:8002"
self.http_client = httpx.AsyncClient(timeout=5.0)
@circuit(failure_threshold=5, recovery_timeout=30)
async def call_order_service(self, path: str, method: str = "GET", **kwargs):
"""Call order service with circuit breaker."""
response = await self.http_client.request(
method,
f"{self.order_service_url}{path}",
**kwargs
)
response.raise_for_status()
return response.json()
async def create_order_aggregate(self, order_id: str) -> dict:
"""Aggregate data from multiple services."""
# Parallel requests
order, payment, inventory = await asyncio.gather(
self.call_order_service(f"/orders/{order_id}"),
self.call_payment_service(f"/payments/order/{order_id}"),
self.call_inventory_service(f"/reservations/order/{order_id}"),
return_exceptions=True
)
# Handle partial failures
result = {"order": order}
if not isinstance(payment, Exception):
result["payment"] = payment
if not isinstance(inventory, Exception):
result["inventory"] = inventory
return result
@app.post("/api/orders")
async def create_order(
order_data: dict,
gateway: APIGateway = Depends()
):
"""API Gateway endpoint."""
try:
# Route to order service
order = await gateway.call_order_service(
"/orders",
method="POST",
json=order_data
)
return {"order": order}
except httpx.HTTPError as e:
raise HTTPException(status_code=503, detail="Order service unavailable")
Communication Patterns
Pattern 1: Synchronous REST Communication
# Service A calls Service B
import httpx
from tenacity import retry, stop_after_attempt, wait_exponential
class ServiceClient:
"""HTTP client with retries and timeout."""
def __init__(self, base_url: str):
self.base_url = base_url
self.client = httpx.AsyncClient(
timeout=httpx.Timeout(5.0, connect=2.0),
limits=httpx.Limits(max_keepalive_connections=20)
)
@retry(
stop=stop_after_attempt(3),
wait=wait_exponential(multiplier=1, min=2, max=10)
)
async def get(self, path: str, **kwargs):
"""GET with automatic retries."""
response = await self.client.get(f"{self.base_url}{path}", **kwargs)
response.raise_for_status()
return response.json()
async def post(self, path: str, **kwargs):
"""POST request."""
response = await self.client.post(f"{self.base_url}{path}", **kwargs)
response.raise_for_status()
return response.json()
# Usage
payment_client = ServiceClient("http://payment-service:8001")
result = await payment_client.post("/payments", json=payment_data)
Pattern 2: Asynchronous Event-Driven
# Event-driven communication with Kafka
from aiokafka import AIOKafkaProducer, AIOKafkaConsumer
import json
from dataclasses import dataclass, asdict
from datetime import datetime
@dataclass
class DomainEvent:
event_id: str
event_type: str
aggregate_id: str
occurred_at: datetime
data: dict
class EventBus:
"""Event publishing and subscription."""
def __init__(self, bootstrap_servers: List[str]):
self.bootstrap_servers = bootstrap_servers
self.producer = None
async def start(self):
self.producer = AIOKafkaProducer(
bootstrap_servers=self.bootstrap_servers,
value_serializer=lambda v: json.dumps(v).encode()
)
await self.producer.start()
async def publish(self, event: DomainEvent):
"""Publish event to Kafka topic."""
topic = event.event_type
await self.producer.send_and_wait(
topic,
value=asdict(event),
key=event.aggregate_id.encode()
)
async def subscribe(self, topic: str, handler: callable):
"""Subscribe to events."""
consumer = AIOKafkaConsumer(
topic,
bootstrap_servers=self.bootstrap_servers,
value_deserializer=lambda v: json.loads(v.decode()),
group_id="my-service"
)
await consumer.start()
try:
async for message in consumer:
event_data = message.value
await handler(event_data)
finally:
await consumer.stop()
# Order Service publishes event
async def create_order(order_data: dict):
order = await save_order(order_data)
event = DomainEvent(
event_id=str(uuid.uuid4()),
event_type="OrderCreated",
aggregate_id=order.id,
occurred_at=datetime.now(),
data={
"order_id": order.id,
"customer_id": order.customer_id,
"total": order.total
}
)
await event_bus.publish(event)
# Inventory Service listens for OrderCreated
async def handle_order_created(event_data: dict):
"""React to order creation."""
order_id = event_data["data"]["order_id"]
items = event_data["data"]["items"]
# Reserve inventory
await reserve_inventory(order_id, items)
Pattern 3: Saga Pattern (Distributed Transactions)
# Saga orchestration for order fulfillment
from enum import Enum
from typing import List, Callable
class SagaStep:
"""Single step in saga."""
def __init__(
self,
name: str,
action: Callable,
compensation: Callable
):
self.name = name
self.action = action
self.compensation = compensation
class SagaStatus(Enum):
PENDING = "pending"
COMPLETED = "completed"
COMPENSATING = "compensating"
FAILED = "failed"
class OrderFulfillmentSaga:
"""Orchestrated saga for order fulfillment."""
def __init__(self):
self.steps: List[SagaStep] = [
SagaStep(
"create_order",
action=self.create_order,
compensation=self.cancel_order
),
SagaStep(
"reserve_inventory",
action=self.reserve_inventory,
compensation=self.release_inventory
),
SagaStep(
"process_payment",
action=self.process_payment,
compensation=self.refund_payment
),
SagaStep(
"confirm_order",
action=self.confirm_order,
compensation=self.cancel_order_confirmation
)
]
async def execute(self, order_data: dict) -> SagaResult:
"""Execute saga steps."""
completed_steps = []
context = {"order_data": order_data}
try:
for step in self.steps:
# Execute step
result = await step.action(context)
if not result.success:
# Compensate
await self.compensate(completed_steps, context)
return SagaResult(
status=SagaStatus.FAILED,
error=result.error
)
completed_steps.append(step)
context.update(result.data)
return SagaResult(status=SagaStatus.COMPLETED, data=context)
except Exception as e:
# Compensate on error
await self.compensate(completed_steps, context)
return SagaResult(status=SagaStatus.FAILED, error=str(e))
async def compensate(self, completed_steps: List[SagaStep], context: dict):
"""Execute compensating actions in reverse order."""
for step in reversed(completed_steps):
try:
await step.compensation(context)
except Exception as e:
# Log compensation failure
print(f"Compensation failed for {step.name}: {e}")
# Step implementations
async def create_order(self, context: dict) -> StepResult:
order = await order_service.create(context["order_data"])
return StepResult(success=True, data={"order_id": order.id})
async def cancel_order(self, context: dict):
await order_service.cancel(context["order_id"])
async def reserve_inventory(self, context: dict) -> StepResult:
result = await inventory_service.reserve(
context["order_id"],
context["order_data"]["items"]
)
return StepResult(
success=result.success,
data={"reservation_id": result.reservation_id}
)
async def release_inventory(self, context: dict):
await inventory_service.release(context["reservation_id"])
async def process_payment(self, context: dict) -> StepResult:
result = await payment_service.charge(
context["order_id"],
context["order_data"]["total"]
)
return StepResult(
success=result.success,
data={"transaction_id": result.transaction_id},
error=result.error
)
async def refund_payment(self, context: dict):
await payment_service.refund(context["transaction_id"])
Resilience Patterns
Circuit Breaker Pattern
from enum import Enum
from datetime import datetime, timedelta
from typing import Callable, Any
class CircuitState(Enum):
CLOSED = "closed" # Normal operation
OPEN = "open" # Failing, reject requests
HALF_OPEN = "half_open" # Testing if recovered
class CircuitBreaker:
"""Circuit breaker for service calls."""
def __init__(
self,
failure_threshold: int = 5,
recovery_timeout: int = 30,
success_threshold: int = 2
):
self.failure_threshold = failure_threshold
self.recovery_timeout = recovery_timeout
self.success_threshold = success_threshold
self.failure_count = 0
self.success_count = 0
self.state = CircuitState.CLOSED
self.opened_at = None
async def call(self, func: Callable, *args, **kwargs) -> Any:
"""Execute function with circuit breaker."""
if self.state == CircuitState.OPEN:
if self._should_attempt_reset():
self.state = CircuitState.HALF_OPEN
else:
raise CircuitBreakerOpenError("Circuit breaker is open")
try:
result = await func(*args, **kwargs)
self._on_success()
return result
except Exception as e:
self._on_failure()
raise
def _on_success(self):
"""Handle successful call."""
self.failure_count = 0
if self.state == CircuitState.HALF_OPEN:
self.success_count += 1
if self.success_count >= self.success_threshold:
self.state = CircuitState.CLOSED
self.success_count = 0
def _on_failure(self):
"""Handle failed call."""
self.failure_count += 1
if self.failure_count >= self.failure_threshold:
self.state = CircuitState.OPEN
self.opened_at = datetime.now()
if self.state == CircuitState.HALF_OPEN:
self.state = CircuitState.OPEN
self.opened_at = datetime.now()
def _should_attempt_reset(self) -> bool:
"""Check if enough time passed to try again."""
return (
datetime.now() - self.opened_at
> timedelta(seconds=self.recovery_timeout)
)
# Usage
breaker = CircuitBreaker(failure_threshold=5, recovery_timeout=30)
async def call_payment_service(payment_data: dict):
return await breaker.call(
payment_client.process_payment,
payment_data
)