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.
git clone --depth 1 https://github.com/Amey-Thakur/AI-SKILLSWrote 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/commands/amey-thakur/ai-skills/plan)<a href="https://agentmods.dev/commands/amey-thakur/ai-skills/plan"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/plan/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/commands/amey-thakur/ai-skills/plan"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00032 | $0.00313 |
| Opus 5 | $0.00016 | $0.00156 |
| Sonnet 5 | $0.00006 | $0.00063 |
| Haiku 4.5 | $0.00003 | $0.00031 |
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 6d 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.
What it actually says
You were invoked as a slash command. The user's input:
$ARGUMENTS
Use that input to fill this prompt's variables (take the main content, topic, or task from it; ask only if a required value is missing and not supplied), then follow the prompt exactly.
Make a plan for: {objective}
Context: {context}
Produce:
- The goal and what done looks like, stated concretely.
- The steps in order, grouped into milestones for anything sizable, with dependencies noted (what must happen before what) and what can go in parallel.
- The risks and unknowns: what could go wrong or block progress, and how to handle each. Flag the parts you are least sure about.
- The first concrete action to take now.
Rules: realistic over ambitious (account for the work people forget: testing, review, the unexpected). Order by dependency and priority. Keep steps concrete and actionable, not vague topics. Right-size the plan to the objective: a small task needs a short list, a project needs milestones. If the objective is too vague to plan, ask what would clarify it. For decomposing a big task into subtasks see break-down-task; for an agent to execute a goal autonomously see the goal prompt.
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.
- 6d ago First seen · 36 lines · 32 tokens per session scan A dccd50973115
plan is a command published in the GitHub repository Amey-Thakur/AI-SKILLS (7 stars, last pushed 7d ago), licensed MIT. It adds 32 tokens to every session and 313 once invoked, about $0.0002 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 2026-09-06.
Other commands, from other repositories
close
They operate it without you.
create-ticket
Create a work-item ticket (GitHub issue / Jira) from an existing requirements.md, then promote its draft spec folder to docs/specs/ /.
finish-tasks
Finalize a work item after all tasks are done — cleanup (currently closing the ticket) and mark the work complete.
work-status
Report the current status of a work item by reading its spec files (requirements/design/tasks) and execution log. Read-only.
/opsx-apply
Implement tasks from an OpenSpec change (Experimental).
align
Align cross-functional stakeholders.