Files
wshobson-agents/plugins/python-development/skills/python-resource-management/SKILL.md
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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

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6.8 KiB
Markdown

---
name: python-resource-management
description: Python resource management with context managers, cleanup patterns, and streaming. Use when managing connections, file handles, implementing cleanup logic, or building streaming responses with accumulated state.
---
# Python Resource Management
Manage resources deterministically using context managers. Resources like database connections, file handles, and network sockets should be released reliably, even when exceptions occur.
## When to Use This Skill
- Managing database connections and connection pools
- Working with file handles and I/O
- Implementing custom context managers
- Building streaming responses with state
- Handling nested resource cleanup
- Creating async context managers
## Core Concepts
### 1. Context Managers
The `with` statement ensures resources are released automatically, even on exceptions.
### 2. Protocol Methods
`__enter__`/`__exit__` for sync, `__aenter__`/`__aexit__` for async resource management.
### 3. Unconditional Cleanup
`__exit__` always runs, regardless of whether an exception occurred.
### 4. Exception Handling
Return `True` from `__exit__` to suppress exceptions, `False` to propagate them.
## Quick Start
```python
from contextlib import contextmanager
@contextmanager
def managed_resource():
resource = acquire_resource()
try:
yield resource
finally:
resource.cleanup()
with managed_resource() as r:
r.do_work()
```
## Fundamental Patterns
### Pattern 1: Class-Based Context Manager
Implement the context manager protocol for complex resources.
```python
class DatabaseConnection:
"""Database connection with automatic cleanup."""
def __init__(self, dsn: str) -> None:
self._dsn = dsn
self._conn: Connection | None = None
def connect(self) -> None:
"""Establish database connection."""
self._conn = psycopg.connect(self._dsn)
def close(self) -> None:
"""Close connection if open."""
if self._conn is not None:
self._conn.close()
self._conn = None
def __enter__(self) -> "DatabaseConnection":
"""Enter context: connect and return self."""
self.connect()
return self
def __exit__(
self,
exc_type: type[BaseException] | None,
exc_val: BaseException | None,
exc_tb: TracebackType | None,
) -> None:
"""Exit context: always close connection."""
self.close()
# Usage with context manager (preferred)
with DatabaseConnection(dsn) as db:
result = db.execute(query)
# Manual management when needed
db = DatabaseConnection(dsn)
db.connect()
try:
result = db.execute(query)
finally:
db.close()
```
### Pattern 2: Async Context Manager
For async resources, implement the async protocol.
```python
class AsyncDatabasePool:
"""Async database connection pool."""
def __init__(self, dsn: str, min_size: int = 1, max_size: int = 10) -> None:
self._dsn = dsn
self._min_size = min_size
self._max_size = max_size
self._pool: asyncpg.Pool | None = None
async def __aenter__(self) -> "AsyncDatabasePool":
"""Create connection pool."""
self._pool = await asyncpg.create_pool(
self._dsn,
min_size=self._min_size,
max_size=self._max_size,
)
return self
async def __aexit__(
self,
exc_type: type[BaseException] | None,
exc_val: BaseException | None,
exc_tb: TracebackType | None,
) -> None:
"""Close all connections in pool."""
if self._pool is not None:
await self._pool.close()
async def execute(self, query: str, *args) -> list[dict]:
"""Execute query using pooled connection."""
async with self._pool.acquire() as conn:
return await conn.fetch(query, *args)
# Usage
async with AsyncDatabasePool(dsn) as pool:
users = await pool.execute("SELECT * FROM users WHERE active = $1", True)
```
### Pattern 3: Using @contextmanager Decorator
Simplify context managers with the decorator for straightforward cases.
```python
from contextlib import contextmanager, asynccontextmanager
import time
import structlog
logger = structlog.get_logger()
@contextmanager
def timed_block(name: str):
"""Time a block of code."""
start = time.perf_counter()
try:
yield
finally:
elapsed = time.perf_counter() - start
logger.info(f"{name} completed", duration_seconds=round(elapsed, 3))
# Usage
with timed_block("data_processing"):
process_large_dataset()
@asynccontextmanager
async def database_transaction(conn: AsyncConnection):
"""Manage database transaction."""
await conn.execute("BEGIN")
try:
yield conn
await conn.execute("COMMIT")
except Exception:
await conn.execute("ROLLBACK")
raise
# Usage
async with database_transaction(conn) as tx:
await tx.execute("INSERT INTO users ...")
await tx.execute("INSERT INTO audit_log ...")
```
### Pattern 4: Unconditional Resource Release
Always clean up resources in `__exit__`, regardless of exceptions.
```python
class FileProcessor:
"""Process file with guaranteed cleanup."""
def __init__(self, path: str) -> None:
self._path = path
self._file: IO | None = None
self._temp_files: list[Path] = []
def __enter__(self) -> "FileProcessor":
self._file = open(self._path, "r")
return self
def __exit__(
self,
exc_type: type[BaseException] | None,
exc_val: BaseException | None,
exc_tb: TracebackType | None,
) -> None:
"""Clean up all resources unconditionally."""
# Close main file
if self._file is not None:
self._file.close()
# Clean up any temporary files
for temp_file in self._temp_files:
try:
temp_file.unlink()
except OSError:
pass # Best effort cleanup
# Return None/False to propagate any exception
```
## Detailed worked examples and patterns
Detailed sections (starting with `## Advanced Patterns`) live in `references/details.md`. Read that file when the navigation summary above is insufficient.
## Best Practices Summary
1. **Always use context managers** - For any resource that needs cleanup
2. **Clean up unconditionally** - `__exit__` runs even on exception
3. **Don't suppress unexpectedly** - Return `False` unless suppression is intentional
4. **Use @contextmanager** - For simple resource patterns
5. **Implement both protocols** - Support `with` and manual management
6. **Use ExitStack** - For dynamic numbers of resources
7. **Accumulate efficiently** - List + join, not string concatenation
8. **Track metrics** - Time-to-first-byte matters for streaming
9. **Document behavior** - Especially exception suppression
10. **Test cleanup paths** - Verify resources are released on errors