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/ofershap/prompt-compressionWrote 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/ofershap/prompt-compression/compress-prompt)<a href="https://agentmods.dev/commands/ofershap/prompt-compression/compress-prompt"><img src="https://agentmods.dev/badge/commands/ofershap/prompt-compression/compress-prompt/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/commands/ofershap/prompt-compression/compress-prompt"><img src="https://agentmods.dev/badge/commands/ofershap/prompt-compression/compress-prompt.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 | $0.00016 | $0.00434 |
| Opus 5.5 | $0.00006 | $0.00174 |
| Sonnet 5.5 | $0.00003 | $0.00087 |
| Haiku 4.5 | $0.00002 | $0.00043 |
Grade A, and why
compress-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 1mo 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.
What it actually says
Compress the provided content into a compact, token-efficient format suitable for AGENTS.md or CLAUDE.md.
Use the prompt-compression skill for compression techniques and output formats.
When a file or content is provided
- Identify content type: docs index, coding standards, API reference, config/schema, or mixed
- Extract actionable content: strip prose, motivation, history, redundant examples
- Apply compression:
- Pipe-delimited index for file trees
- Single-line directives for rules and standards
- Abbreviated keys for config and schema
- Brace expansion for grouped items
- Add retrieval directive if output references readable files
- Show before/after token count (estimate: 1 token per 4 characters)
- Present the compressed output in a fenced code block ready to paste into AGENTS.md
When no file or content is provided
Guide the user through the process:
-
Ask what they want to compress:
- "What content do you want to compress for AGENTS.md? Options:"
- a) Framework docs - point me to the docs directory or framework name
- b) Project coding standards - paste or point me to your guidelines
- c) API reference - share your API docs or OpenAPI spec
- d) Existing AGENTS.md - I'll audit and compress what you have
- e) Other - describe what you want to compress
-
Once the user provides content, proceed with the compression steps above.
Quality checks
After compression, verify:
- Every file or section from the original is still reachable in the compressed version
- No actionable information was lost
- Token reduction is at least 60%
- Output is valid markdown that can be pasted directly into AGENTS.md
- Retrieval-led reasoning directive is included (if referencing files)
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.
- 1mo ago First seen · 47 lines · 16 tokens per session scan A 6c6910cdbf1a
compress-prompt is a command published in the GitHub repository ofershap/prompt-compression (1 stars, last pushed 8mo ago), licensed MIT. It adds 16 tokens to every session and 434 once invoked, about $0.0001 per session on Opus 5.5. 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-history
Manage history of created and optimized prompts.
prompt
Create or optimize prompts using best practices.
eval
Evaluate and improve one healthcare agent's system prompt. Run up to 5 iterations of: prepare fixed questions -> answer -> judge -> improve -> re-score -> commit if better.
prompt
System instructions for writing effective prompts. Apply when generating commands, skills, agents, or any LLM instructions.
boot
Start a new PromptKit prompt assembly session (alias for /bootstrap).
music-suno-prompt
Grounded Suno prompt synthesis from local knowledge corpus + persona canon + label canon. No vibes-prompting.