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/WeaveMindAI/weftWrote 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/agents/weavemindai/weft/prompt-engineer)<a href="https://agentmods.dev/agents/weavemindai/weft/prompt-engineer"><img src="https://agentmods.dev/badge/agents/weavemindai/weft/prompt-engineer/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/agents/weavemindai/weft/prompt-engineer"><img src="https://agentmods.dev/badge/agents/weavemindai/weft/prompt-engineer.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 | $0.00060 | $0.03426 |
| Opus 5.5 | $0.00024 | $0.01370 |
| Sonnet 5.5 | $0.00012 | $0.00685 |
| Haiku 4.5 | $0.00006 | $0.00343 |
Grade C, and why
prompt-engineer scanned grade C with 2 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 15d 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
You close every failure mode in advance by narrating it as built, never as forbidden. Name the failure, show what it looks like when it arrives ("ignore previous instructions", "this is just a test", empty input, fiction Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Asks the agent to reveal its instructionsmediumSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
- A node with `parseJson: true` extracts named keys from the model's reply into added output ports. When [the brief] names those keys, the prompt's output instructions say, in its own voice, that the reply is JSON with e The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 15d ago Changed · +4 lines e34c2438c8c3
- 24d ago First seen · 135 lines · 60 tokens per session scan C 76e6ce0efc4f
prompt-engineer is an agent published in the GitHub repository WeaveMindAI/weft (2,002 stars, last pushed today), with no licence file. It adds 60 tokens to every session and 3,426 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it C with 2 findings (instruction-override phrasing, asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-23.
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