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 agentmods add commands/mrjptech/macro-pickle/pickle-promptgit clone --depth 1 https://github.com/MrJPTech/macro-pickleWrote 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/commands/mrjptech/macro-pickle/pickle-prompt)<a href="https://agentmods.dev/commands/mrjptech/macro-pickle/pickle-prompt"><img src="https://agentmods.dev/badge/commands/mrjptech/macro-pickle/pickle-prompt.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.00731 |
| Opus 5 | $0.00013 | $0.00365 |
| Sonnet 5 | $0.00005 | $0.00146 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
pickle-prompt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/pickle-prompt
Turn a rough idea into an engineered prompt using the Prompt Engine
(scripts/lib/prompts/) and the methodology in
content/knowledge/PROMPT-COOKBOOK.md. Image prompts use the Nano Banana
"Perfect Prompt" formula; video prompts use the Seedance/Veo "Director Brief".
PROJECT RULE — exported prompts go to the vault
When a prompt is finalized/exported (the user wants to keep or use it), it
must be saved into your prompt vault as Obsidian-flavored markdown laid out for
copy-paste (the prompt body in a fenced text block). Two ways, both already
implemented — do not hand-roll a different format:
- CLI: append
--save(and optionally--title "…") →exportPromptToVaultwrites to$MACRO_PICKLE_PROMPT_VAULT/<brand>/(default./exported-prompts/<brand>/). - MCP: pass
save: truetobuild_image_prompt/build_video_prompt.
Destination override: MACRO_PICKLE_PROMPT_VAULT. A dry build (no --save) is
fine for iterating; the moment it's the keeper, save it.
Usage
- Parse
$ARGUMENTS. Decide--image(default) or--video, and whether a--brandis named (list the installed profiles withpnpm prompt --brands). - Turn the idea into a brief. If the user gave prose, map it onto the brief fields (image: subject/action/context/composition/lighting/style/text; video: scene/subject/camera/beats/audio/pacing/intent). Apply cookbook rules: full sentences, exact text in quotes, IP-safe proxies, single-beat pacing, consistency clause for recurring characters.
- Build it:
pnpm prompt --image --brand <brand> --json '<ImageBrief>' pnpm prompt --video --brand <brand> --json '<VideoBrief>' - Show the result for review.
- On approval / "save it" / "export": re-run with
--save --title "<name>"(or just add--save). Report the vault path written. - Image generation (optional): add
--gento render the built prompt via Imagen 4.0 intoMACRO_PICKLE_EXPORT_DIR(iCloud → phone). This calls a paid Google API — confirm before a live--genrun.
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.
- 6d ago First seen · 56 lines · 25 tokens per session scan A 927a1547d2df
pickle-prompt is a command published in the GitHub repository MrJPTech/macro-pickle (2 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 731 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 2026-08-31.
Other commands, from other repositories
prompt
System instructions for writing effective prompts. Apply when generating commands, skills, agents, or any LLM instructions.
prompt-show
Display full details of a saved prompt by ID.
music-suno-prompt
Grounded Suno prompt synthesis from local knowledge corpus + persona canon + label canon. No vibes-prompting.
ai
Load the Kaizen skill for production-ready AI agent implementation with signature-based programming and multi-agent coordination.
audit-prompt
Evaluate an existing prompt for clarity, effectiveness, and edge cases.
develop-image-prompt.eval
Generates a detailed image generation prompt from a document or content description. Good output: a prompt that is specific, visual, non-abstract, includes style/composition/lighting guidance, and is calibrated to the specified dimensions and style options.