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 commands/softaworks/agent-toolkit/codex-plangit clone --depth 1 https://github.com/softaworks/agent-toolkitWhat 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 | $0.00015 | $0.02668 |
| Opus 5 | $0.00008 | $0.01334 |
| Sonnet 5 | $0.00003 | $0.00534 |
| Haiku 4.5 | $0.00002 | $0.00267 |
Grade B, and why
codex-plan scanned grade B with 1 finding 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 yesterday.
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.
Asks the agent to reveal its instructionsmediumSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
7. **Output instructions** - Write to `codex-plan.md` in current directory How it starts
The opening of the file, as written. The whole thing — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Plan Command
You are being asked to create a detailed implementation plan using a Codex subagent. Your job is to:
- Understand the user's planning request
- Ask clarifying questions using AskUser to improve plan quality
- Craft an excellent, detailed prompt for Codex
- Execute Codex to generate and save the plan
Always uses: gpt-5.2-codex with high reasoning
User Request
$ARGUMENTS
Step 1: Analyze the Request
Look at what the user wants to plan. Identify:
- What is the core goal?
- What technology/domain is involved?
- What aspects are ambiguous or underspecified?
- What decisions would significantly impact the plan?
Step 2: Ask Clarifying Questions
Use AskUser to ask 3-6 targeted clarifying questions before generating the plan.
Good clarifying questions:
- Narrow down scope and requirements
- Clarify technology choices
- Understand constraints (time, budget, team size)
- Identify must-haves vs nice-to-haves
- Uncover integration requirements
- Determine security/compliance needs
Example Question Patterns
For "implement auth":
- What authentication methods do you need? (email/password, OAuth providers like Google/GitHub, SSO, magic links)
- Do you need role-based access control (RBAC) or just authenticated/unauthenticated?
- What's your backend stack? (Node/Express, Python/Django, etc.)
- Where will you store user credentials/sessions? (Database, Redis, JWT stateless)
- Do you need features like: password reset, email verification, 2FA?
- Any compliance requirements? (SOC2, GDPR, HIPAA)
For "build an API":
- What resources/entities does this API need to manage?
- REST or GraphQL?
- What authentication will the API use?
- Expected scale/traffic?
- Do you need rate limiting, caching, versioning?
For "migrate to microservices":
- Which parts of the monolith are you migrating first?
- What's your deployment target? (K8s, ECS, etc.)
- How will services communicate? (REST, gRPC, message queues)
- What's your timeline and team capacity?
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.
- yesterday First seen · 320 lines · 15 tokens per session scan B 0b3c3fc563cb
codex-plan is a command published in the GitHub repository softaworks/agent-toolkit (2,401 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 2,668 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
add-agent
引导新增一个 Agent 适配器。用法 /add-agent.
speckit.archive
Archive a feature specification into main project memory after merge, resolving gaps and conflicts.
speckit.opsmill.retrospect
Run a session retrospective that surfaces context-management gaps and routes them to approved follow-up actions.
create-issue
Transform feature descriptions, bug reports, or improvement ideas into well-structured GitHub issues.
pr
Handle the full workflow from current branch state to an open, CI-monitored pull request.
mach12:issue-review
Read a GitHub issue and all comments, review the implementation plan, and present findings.