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 supatest-ai/alan-skills --skill alan-plangit clone --depth 1 https://github.com/supatest-ai/alan-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/skills/supatest-ai/alan-skills/alan-plan)<a href="https://agentmods.dev/skills/supatest-ai/alan-skills/alan-plan"><img src="https://agentmods.dev/badge/skills/supatest-ai/alan-skills/alan-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/skills/supatest-ai/alan-skills/alan-plan"><img src="https://agentmods.dev/badge/skills/supatest-ai/alan-skills/alan-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00010 | $0.01766 |
| Opus 5.5 | $0.00004 | $0.00706 |
| Sonnet 5.5 | $0.00002 | $0.00353 |
| Haiku 4.5 | $0.00001 | $0.00177 |
Grade A, and why
alan-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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Creation
You are creating an implementation plan. Your job is to analyze the problem and produce a clear, actionable plan in markdown.
How to plan
-
Analyze — Read the task description and any linked context. Explore the codebase to understand architecture, dependencies, constraints, and risks. Use Read, Grep, Glob freely. Do NOT write or modify any files.
If this is a revision request (the user references feedback on an existing plan, or mentions a plan artifact), first fetch the existing plan with
mcp__alan__get_artifactto understand what was already proposed. -
Clarify — Before drafting, assess whether the scope is clear enough to plan against. If it's not — ask questions. One at a time.
This is how a senior engineer operates: they don't guess, they don't silently fill in gaps, they don't plan against assumptions. They ask until they understand. Walk down each branch of the decision tree and resolve ambiguity before committing it to a plan.
- Ask one question per message. Don't dump a list of 10 questions.
- If a question can be answered by exploring the codebase, explore instead of asking.
- If the scope or requirements are genuinely unclear, say so directly: "I need more clarity on X before I can plan this well."
- Don't be hesitant about asking. It's not friction — it's quality control. A plan built on assumptions is worse than no plan.
Break-glass: when to skip this step. If the task description is detailed, subtasks are clear, related documents exist, and the codebase exploration answered your open questions — go straight to Draft. Don't force clarification when none is needed. Read the room.
-
Draft — Write your plan as natural free-form markdown. Structure it however makes sense for this specific problem:
- Bullet list of steps
- Phased breakdown with dependencies
- Decision tree with trade-offs
- File-by-file change list
- Whatever communicates the plan most clearly
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.
- 2mo ago First seen · 159 lines · 10 tokens per session scan A 5e246fd8e059
alan-plan is a skill published in the GitHub repository supatest-ai/alan-skills (0 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 10 tokens to every session and 1,766 once invoked, about $0.0000 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 2026-09-01.
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