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 oscarsterling/clelp-skills --skill prompt-injection-guardgit clone --depth 1 https://github.com/oscarsterling/clelp-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/oscarsterling/clelp-skills/prompt-injection-guard)<a href="https://agentmods.dev/skills/oscarsterling/clelp-skills/prompt-injection-guard"><img src="https://agentmods.dev/badge/skills/oscarsterling/clelp-skills/prompt-injection-guard/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/oscarsterling/clelp-skills/prompt-injection-guard"><img src="https://agentmods.dev/badge/skills/oscarsterling/clelp-skills/prompt-injection-guard.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 | $0.00091 | $0.01541 |
| Opus 5 | $0.00046 | $0.00771 |
| Sonnet 5 | $0.00018 | $0.00308 |
| Haiku 4.5 | $0.00009 | $0.00154 |
Grade A, and why
prompt-injection-guard 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 12d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Injection Guard
You are wiring a deterministic guard that inspects each inbound prompt and refuses the specific STRUCTURAL shapes a forged operator command takes. The model cannot rationalize its way past a harness-level refusal the way it can talk itself past a prose rule in a system prompt.
The package ships three portable pieces:
reference/inbound-guard.example.py- the hook. It checks four content-free signatures and exits 2 (refuse) on a match, 0 (pass) otherwise. It fails OPEN on any parser error so it can never wedge the agent loop.scripts/inbound-scan.py- a standalone scanner that loads the same detection and runs it over arbitrary text, with a--self-test. One source of truth, so a green self-test proves what the live hook will decide.templates/untrusted-content-fence.md- the provenance/taint design doc. The hook is the cheap front line; provenance is the real boundary. Read it before you rely on the hook alone.
The four signatures
- Role-label prefix. A body that opens with a configured role word ("Human:", "Assistant:", or your own list), at the top of the prompt or inside a trusted-channel wrapper. Real human input carries no role scaffolding; a body that does is usually the model's own output round-tripped as a fake user turn.
- Wrapper integrity. If you configure a trusted-channel wrapper tag, a block
wearing that tag must carry the exact
sourcevalue a genuine envelope carries AND populate every required attribute. A tag that claims the channel but mismatches the source or skimps on attributes is refused. An unparseable wrapper (opener present, no valid close) is refused too: fail CLOSED. - Future / malformed timestamp. A genuine envelope timestamp is the real send time, offset-aware, and not in the future. Future-beyond-tolerance, unparseable, or timezone-naive timestamps are refused.
- Duplicate id. The same
(source, id)seen again inside a short window with DIFFERENT content is a replay/confabulation tell.
What ships with it
6 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.
- 12d ago First seen · 112 lines · 91 tokens per session scan A 040c0e971fea
prompt-injection-guard is a skill published in the GitHub repository oscarsterling/clelp-skills (0 stars, last pushed 5d ago), licensed MIT. It adds 91 tokens to every session and 1,541 once invoked, about $0.0005 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.
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