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/felipeslo/opencode-kit/plangit clone --depth 1 https://github.com/felipeslo/opencode-kitWhat 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 | $0.00018 | $0.00526 |
| Opus 5 | $0.00009 | $0.00263 |
| Sonnet 5 | $0.00004 | $0.00105 |
| Haiku 4.5 | $0.00002 | $0.00053 |
Grade A, and why
plan 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 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.
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.
What it actually says
/plan - Project Planning Mode
$ARGUMENTS
🔴 CRITICAL RULES
- NO CODE WRITING - This command creates plan file only
- Use project-planner agent - NOT OpenCode's native Plan mode
- Socratic Gate - Ask clarifying questions before planning
- Dynamic Naming - Plan file named based on task
Task
Use the project-planner agent with this context:
CONTEXT:
- User Request: $ARGUMENTS
- Mode: PLANNING ONLY (no code)
- Output: docs/PLAN-{task-slug}.md (dynamic naming)
NAMING RULES:
1. Extract 2-3 key words from request
2. Lowercase, hyphen-separated
3. Max 30 characters
4. Example: "e-commerce cart" → PLAN-ecommerce-cart.md
RULES:
1. Follow project-planner.md Phase -1 (Context Check)
2. Follow project-planner.md Phase 0 (Socratic Gate)
3. Create PLAN-{slug}.md with task breakdown
4. DO NOT write any code files
5. REPORT the exact file name created
Expected Output
| Deliverable | Location |
|---|---|
| Project Plan | docs/PLAN-{task-slug}.md |
| Task Breakdown | Inside plan file |
| Agent Assignments | Inside plan file |
| Verification Checklist | Phase X in plan file |
After Planning
Tell user:
[OK] Plan created: docs/PLAN-{slug}.md
Next steps:
- Review the plan
- Run `/create` to start implementation
- Or modify plan manually
Naming Examples
| Request | Plan File |
|---|---|
/plan e-commerce site with cart |
docs/PLAN-ecommerce-cart.md |
/plan mobile app for fitness |
docs/PLAN-fitness-app.md |
/plan add dark mode feature |
docs/PLAN-dark-mode.md |
/plan fix authentication bug |
docs/PLAN-auth-fix.md |
/plan SaaS dashboard |
docs/PLAN-saas-dashboard.md |
Usage
/plan e-commerce site with cart
/plan mobile app for fitness tracking
/plan SaaS dashboard with analytics
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 · 90 lines · 18 tokens per session scan A c50bb2e46949
plan is a command published in the GitHub repository felipeslo/opencode-kit (2 stars, last pushed 5mo ago), licensed MIT. It adds 18 tokens to every session and 526 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.