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 sigistry/marketplace --skill prompt-versioning-hygienegit clone --depth 1 https://github.com/sigistry/marketplaceWrote 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/sigistry/marketplace/prompt-versioning-hygiene)<a href="https://agentmods.dev/skills/sigistry/marketplace/prompt-versioning-hygiene"><img src="https://agentmods.dev/badge/skills/sigistry/marketplace/prompt-versioning-hygiene/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/sigistry/marketplace/prompt-versioning-hygiene"><img src="https://agentmods.dev/badge/skills/sigistry/marketplace/prompt-versioning-hygiene.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 | $0.00075 | $0.00838 |
| Opus 5 | $0.00037 | $0.00419 |
| Sonnet 5 | $0.00015 | $0.00168 |
| Haiku 4.5 | $0.00007 | $0.00084 |
Grade A, and why
prompt-versioning-hygiene 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 8d 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Versioning Hygiene
Purpose
Prompts are the highest-leverage, least-governed artifact in most LLM apps: a one-line edit to a system prompt can change behavior across every request, yet prompts are typically inline string literals that ship with no version, no review, and no test. This skill standardizes treating prompts as code, externalized, versioned, diffable, reviewed, and tested, so a prompt change is a deliberate, traceable, gated event instead of a silent regression waiting to happen. It is the connective tissue between the eval-authoring skill (which grades prompts) and the day-to-day discipline of changing them.
The core problem: prompts as magic strings
# The anti-pattern: prompt buried in logic, no version, no test, no review trail
def summarize(doc):
return llm(f"You are a helpful assistant. Summarize this in 3 bullets: {doc}")
Nothing here can be diffed meaningfully, reviewed as a unit, rolled back independently, or A/B-tested. A behavior change and a prompt change are indistinguishable in the git history. The fix is to give every prompt an identity.
The hygiene checklist
| Practice | Why it matters |
|---|---|
| Externalize prompts from logic (dedicated files/modules or a prompt registry) | Makes prompts findable, diffable, and reviewable on their own |
| Version each prompt (semantic version or content hash) | Lets you pin, roll back, and correlate an output to the exact prompt that produced it |
| Review prompt changes like code (PR, required approval) | A prompt edit is a behavior change; it deserves the same gate as a code change |
| Test every prompt against the eval suite before merge | Proves the change improved rather than regressed (see eval-authoring) |
| Separate prompt data from prompt logic | Keep the template text apart from the interpolation/assembly code |
| Environment-aware rendering (dev/staging/prod) | Iterate safely without touching production behavior |
| Log the version with each request | An incident is traceable to the exact prompt version live at the time |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 47 lines · 75 tokens per session scan A 204b8746dd5c
prompt-versioning-hygiene is a skill published in the GitHub repository sigistry/marketplace (3 stars, last pushed today), licensed MIT. It adds 75 tokens to every session and 838 once invoked, about $0.0004 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 2026-09-03.
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