Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/zm1990s/kb-agent/plugin-creatornpx skills add zm1990s/kb-agent --skill plugin-creatorgit clone --depth 1 https://github.com/zm1990s/kb-agentWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00086 | $0.02422 |
| Opus 5 | $0.00043 | $0.01211 |
| Sonnet 5 | $0.00017 | $0.00484 |
| Haiku 4.5 | $0.00009 | $0.00242 |
Grade A, and why
plugin-creator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
98% identical to plugin-creator — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plugin Creator
Quick Start
- Run the scaffold script:
# Plugin names are normalized to lower-case hyphen-case and must be <= 64 chars.
# The generated folder and plugin.json name are always the same.
# Run from the skill root (the directory containing this `SKILL.md`).
# By default creates in `~/plugins/<plugin-name>`.
python3 scripts/create_basic_plugin.py <plugin-name>
-
Edit
<plugin-path>/.codex-plugin/plugin.jsonwhen the request gives specific metadata. The scaffold starts with valid defaults and must not contain[TODO: ...]placeholders. -
Generate or update the personal marketplace entry when the plugin should appear in Codex UI ordering:
# Personal marketplace entries default to `~/.agents/plugins/marketplace.json`.
python3 scripts/create_basic_plugin.py my-plugin --with-marketplace
Only specify --marketplace-name <name> when the default personal marketplace name is already
taken or installed and you need to seed a different new marketplace file:
python3 scripts/create_basic_plugin.py my-plugin \
--with-marketplace \
--marketplace-name team-local
Only use a repo/team marketplace when the user specifically asks for that destination:
python3 scripts/create_basic_plugin.py my-plugin \
--path <repo-root>/plugins \
--marketplace-path <repo-root>/.agents/plugins/marketplace.json \
--with-marketplace
When the user specifies a marketplace path, make sure that marketplace is actually installed before
telling the user to reinstall from it. The default personal marketplace file at
~/.agents/plugins/marketplace.json is discovered implicitly, but other marketplace paths are not.
On Windows, use the equivalent path under the user profile.
- Generate/adjust optional companion folders as needed:
python3 scripts/create_basic_plugin.py my-plugin \
--path <parent-plugin-directory> \
--marketplace-path <marketplace-json-path> \
--with-skills --with-hooks --with-scripts --with-assets --with-mcp --with-apps --with-marketplace
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 339 B
- assets/plugin-creator-small.svg 1.3 KB
- assets/plugin-creator.png 1.5 KB
- references/installing-and-updating.md 5.7 KB
- references/plugin-json-spec.md 9.0 KB
- scripts/create_basic_plugin.py 11 KB runs code
- scripts/read_marketplace_name.py 1.5 KB runs code
- scripts/update_plugin_cachebuster.py 2.6 KB runs code
- scripts/validate_plugin.py 21 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 244 lines · 86 tokens per session scan A 8fd56316b2c4
plugin-creator is a skill published in the GitHub repository zm1990s/kb-agent (5 stars, last pushed 12d ago), licensed MIT. It adds 86 tokens to every session and 2,422 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to plugin-creator, differing in 12 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.