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 alivirgo/Major-AI-Skills --skill artifact-reuse-patterngit clone --depth 1 https://github.com/alivirgo/Major-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/skills/alivirgo/major-ai-skills/artifact-reuse-pattern)<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/artifact-reuse-pattern"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/artifact-reuse-pattern/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/alivirgo/major-ai-skills/artifact-reuse-pattern"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/artifact-reuse-pattern.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 | $0.00027 | $0.01165 |
| Opus 5 | $0.00014 | $0.00583 |
| Sonnet 5 | $0.00005 | $0.00233 |
| Haiku 4.5 | $0.00003 | $0.00117 |
Grade A, and why
artifact-reuse-pattern 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 today.
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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persistent Living Artifact Mutation Pattern
Overview
When executing multi-phase engineering tasks, poorly designed agents generate new markdown files for every status update (plan_v1.md, plan_v2.md, revised_plan.md, final_summary.md).
Creating duplicate files pollutes repository search indices, degrades RAG vector embeddings, confuses subagents with conflicting historical drafts, and wastes thousands of generation tokens.
The Persistent Living Artifact Pattern enforces a single canonical document per domain (e.g. implementation_plan.md, walkthrough.md) and updates it via in-place differential edits (replace_file_content), maintaining a pristine single source of truth.
Duplicate Proliferation vs. Single Living Artifact
┌─────────────────────────────────────────────────────────────┐
│ Artifact Lifecycle Comparison │
│ │
│ Duplicate Proliferation (Anti-Pattern): │
│ • Turn 1: `write_to_file("plan_v1.md")` (800 tokens) │
│ • Turn 5: `write_to_file("plan_v2.md")` (950 tokens) │
│ • Turn 12: `write_to_file("final_plan.md")` (1,100 tokens) │
│ ↳ 3 duplicate files in repo, 2,850 tokens billed │
│ │
│ Single Living Artifact (Living Mutation Pattern): │
│ • Turn 1: `write_to_file("implementation_plan.md")` │
│ • Turn 5: `replace_file_content("implementation_plan.md")` │
│ ↳ Mutates only the completed phase (45 tokens!) │
│ • Turn 12: Updates verification status in place │
│ ↳ 1 canonical file, 92% fewer mutation tokens billed │
└─────────────────────────────────────────────────────────────┘
The 3 Canonical Agent Artifacts
In standard agentic frameworks (Antigravity IDE, Claude Code, Cursor), maintain strictly 3 canonical state documents in the artifact directory:
| Artifact | Purpose | Lifecycle State |
|---|---|---|
implementation_plan.md |
Technical architecture, step-by-step roadmap, open questions, and verification gates. | Updated in-place as each milestone completes. |
walkthrough.md |
Final user-facing demo, completed changes diffs, validation logs, and media recordings. | Appended/updated as milestones pass verification. |
scratch/notes.md |
Temporary scratchpad for ephemeral CLI outputs or quick math. | Disposable; never referenced in user plans. |
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.
- today Changed · -4 tokens per session 408326df64bf
- 6d ago First seen · 115 lines · 31 tokens per session scan A 52dd7bf6b813
artifact-reuse-pattern is a skill published in the GitHub repository alivirgo/Major-AI-Skills (1 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 1,165 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 2026-09-05.
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