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 rp1-run/rp1 --skill tersify-promptgit clone --depth 1 https://github.com/rp1-run/rp1Wrote 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/rp1-run/rp1/tersify-prompt)<a href="https://agentmods.dev/skills/rp1-run/rp1/tersify-prompt"><img src="https://agentmods.dev/badge/skills/rp1-run/rp1/tersify-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/skills/rp1-run/rp1/tersify-prompt"><img src="https://agentmods.dev/badge/skills/rp1-run/rp1/tersify-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 | $0.00021 | $0.00707 |
| Opus 5 | $0.00010 | $0.00353 |
| Sonnet 5 | $0.00004 | $0.00141 |
| Haiku 4.5 | $0.00002 | $0.00071 |
Grade A, and why
tersify-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 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.
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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tersify Prompt
Compresses agent-instruction prompts to be maximally terse while preserving full intent.
Modes
File Mode (when INPUT is a valid file path):
- Read the file content
- Pass to tersifier agent
- Extract compressed prompt from output
- Update the file with compressed version
- Display change summary
Inline Mode (when INPUT is prompt text):
- Pass prompt directly to tersifier agent
- Display compressed prompt and change log
Workflow
Step 1: Detect Mode
Check if INPUT is a file path:
Use Bash: test -f "{INPUT}" && echo "file" || echo "inline"
Step 2: Prepare Input
If file mode:
- Read the file using Read tool
- Store the file path for later update
- Extract file content as INPUT_PROMPT
If inline mode:
- Use INPUT directly as INPUT_PROMPT
Step 3: Spawn Tersifier Agent
{% dispatch_agent "rp1-utils:prompt-tersifier" %} {INPUT_PROMPT content here} {% enddispatch_agent %}
Step 4: Process Output
The agent returns output in this format:
<<<COMPRESSED_PROMPT
[compressed content]
COMPRESSED_PROMPT>>>
<<<CHANGES
[op] ref: description
- from: "short excerpt"
- to: "short excerpt"
- note: reason
[op] ref: description
...
CHANGES>>>
Parse the output:
- Extract content between
<<<COMPRESSED_PROMPTandCOMPRESSED_PROMPT>>> - Extract the changes list between
<<<CHANGESandCHANGES>>>
Step 5: Finalize
If file mode:
- Use Write tool to update the original file with the compressed prompt
- Display to user:
Updated: {file_path} ## Changes Made {changes table}
If inline mode:
- Display to user:
## Compressed Prompt {compressed prompt} ## Changes Made {changes table}
Examples
File mode:
/tersify-prompt plugins/base/agents/kb-spatial-analyzer.md
Output: Updates file in place, shows change summary.
Inline mode:
/tersify-prompt "You are a helpful assistant that helps users write code. Always be polite and thorough in your responses. Make sure to explain your reasoning step by step."
Output: Displays compressed prompt and change log.
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 · 123 lines · 21 tokens per session scan A fe17c475043f
tersify-prompt is a skill published in the GitHub repository rp1-run/rp1 (38 stars, last pushed 4d ago), licensed Apache-2.0. It adds 21 tokens to every session and 707 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 2026-09-07.
Other skills, from other repositories
refine
Transform a brief or prompt into a structured, production-ready prompt via prompt-optimizer. File or text mode.
prompt-optimization
Improves LLM-facing context while preserving intent, execution boundaries, and proportional work. Use when creating or reviewing prompts, agent definitions, skill definitions, or other instructions for an LLM.
recipe-eval-prompt
Compares original and optimized prompts through repeated blind paired execution in git worktrees. Use when evaluating prompt improvement effects or learning prompt engineering through concrete examples.
pi-prompting
Internal guidance for composing prompts that Pi runs (DeepSeek by default) handle reliably for coding, review, diagnosis, and research tasks.
analyze-prompt
Use when the user wants to review, score, or improve how they write prompts; when coaching prompt quality; or when tracking prompting mistakes over a session. Keywords: prompt analysis, prompt coaching, how should I ask, rate my prompt, am I prompting well, prompt statistics, prompt score.
prompt-report
Use when the user wants an end-of-session summary of their prompting: overall stats, best and worst prompts, biggest recurring mistake, improvement curve, and personalized recommendations. Keywords: prompt report, session summary, how did I do, my prompting stats, prompt scorecard, prompting progress.