Awesome Codex Plugins is a curated catalogue and marketplace of installable plugins, skills, and related resources for OpenAI Codex and ChatGPT. It helps people find, create, validate, and submit extensions for Codex workflows across its app, command-line interface, and IDE extensions. The catalogue add-ons are the plugins, skills, agents, and hooks listed or supported by this project.
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 skills add hashgraph-online/awesome-codex-plugins --skill review-workgit clone --depth 1 https://github.com/hashgraph-online/awesome-codex-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/review-work)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/review-work"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/review-work/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/review-work"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/review-work.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 178 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What 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 5.1 | $0.00072 | $0.01541 |
| Opus 5.5 | $0.00029 | $0.00616 |
| Sonnet 5.5 | $0.00014 | $0.00308 |
| Haiku 4.5 | $0.00007 | $0.00154 |
Grade A, and why
review-work 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- review-work — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Invoked as
/agiflow:review-work. In hosts without slash-prompts, this skill is triggered by matching intent and drives AgiFlow via its MCP tools.
Usage:
/agiflow:review-work <work-unit-slug-or-id>- Review a specific work unit/agiflow:review-work <task-slug-or-id>- Review a specific task/agiflow:review-work- List completed items for review
Examples:
/agiflow:review-work DXX-WU-1(review work unit by slug)/agiflow:review-work DXX-3(review task by slug)/agiflow:review-work(interactive selection)
Purpose Verify that completed work actually meets its acceptance criteria, catches quality issues, and is ready to ship. AI code has 1.7x more defects than human-written code — review is the last line of defense before shipping.
Guardrails
- Review what exists — do not implement fixes during review (create follow-up tasks instead).
- Every acceptance criterion gets a pass/fail verdict with evidence.
- Flag issues by severity: blocker (must fix), warning (should fix), note (nice to fix).
- Be honest — a "pass" with gaps is worse than a clear "needs rework".
If a work unit or task slug/id is provided, load it with get_work_unit / get_task; otherwise list candidates with list_work_units / list_tasks for selection.
AgiFlow Project Management Guidelines
Follow the shared AgiFlow project-management guidelines in references/agiflow-agents.md — agent assignment, the task status workflow and transitions, work-unit best practices, and the tags strategy apply to this workflow.
Steps
1. Load the Work for Review
If work unit slug/id provided:
- Use
get_work_unitMCP tool to load the work unit and its tasks. - For each task in the work unit, use
get_taskto load full details (acceptance criteria, devInfo, comments).
If task slug/id provided: 3. Use get_task MCP tool to load the task with full details.
If nothing provided: 4. Use list_work_units with status: "completed" to show completed work units. 5. Use list_tasks with status: "Review" or status: "Done" to show completed tasks. 6. Ask user to select what to review.
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.
- 1mo ago First seen · 184 lines · 72 tokens per session scan A 88f3a4a71bd6
review-work is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (1,364 stars, last pushed today), licensed Apache-2.0. It adds 72 tokens to every session and 1,541 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
review-work
Quality gate: verify each acceptance criterion of a completed task/work unit, run quality checks, and create follow-up tasks for gaps. Use before merging or to audit delivered work. Invoked as /agiflow:review-work . Uses getworkunit, gettask, updatetask, createtask, createtaskcomment.
awesome-chatgpt
Search this repository's awesome-ChatGPT-repositories list for open-source ChatGPT and LLM projects such as RAG frameworks, agents, chatbots, CLIs, prompts, and browser extensions. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, or AI development; not for editing or adding list…
awesome-chatgpt-search
Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
review-prs
Triage open PRs — screen from the diff, delegate the admission judgment to audit-the-list, then merge or close on GitHub. Fire when the maintainer asks to review PRs, process the PR queue, or judge whether a specific PR should be merged.
preview-verdicts
Generate the interactive keep/remove/add/reject verdict preview (HTML page with per-row feedback controls) whenever a prune sweep, batch entry edit, or restructure needs maintainer review before touching README.md — and process the feedback JSON the maintainer pastes back.
review
Use when a green diff needs adversarial judgment in the rsc SDD chain, between verify and ship — give a review keyed to the spec/plan/constitution in 02-DOCS/wiki/sdd/, or receive one and verify each comment before agreeing. NOT running lint/type/tests (that is verify), NOT the spec-less standalone pass (that is…