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/shaq1992/muscle-memory/write_promptgit clone --depth 1 https://github.com/shaq1992/muscle-memoryWrote 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/shaq1992/muscle-memory/write_prompt)<a href="https://agentmods.dev/commands/shaq1992/muscle-memory/write_prompt"><img src="https://agentmods.dev/badge/commands/shaq1992/muscle-memory/write_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 | $0.00031 | $0.06325 |
| Opus 5 | $0.00015 | $0.03163 |
| Sonnet 5 | $0.00006 | $0.01265 |
| Haiku 4.5 | $0.00003 | $0.00632 |
Grade B, and why
write_prompt scanned grade B with 1 finding 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 3d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
while executing it -- template ambiguities, missing constraints, incorrect find patterns. Run the shared flow in `.claude/harness/procedures/self_improvement.md` The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 3d ago First seen · 483 lines · 31 tokens per session scan B 3e78a6aca944
write_prompt is a command published in the GitHub repository shaq1992/muscle-memory (5 stars, last pushed 7d ago), with no licence file. It adds 31 tokens to every session and 6,325 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). 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.
prompt-optimize
Present the efficiency-versus-effectiveness frontier as labelled variants and let the user pick. TRIGGER WHEN: the user wants to review or optimize a prompt, system message, or agent instructions for clarity/tokens/reliability.
audit-prompt
Evaluate an existing prompt for clarity, effectiveness, and edge cases.
prompt-create
Create a new prompt following ground rules.
prompt-engineer
Interactive Prompt Engineer - collaborative refinement with best practices and clipboard copy.