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 skills/oriolshhh/runware-image-mcp/context-compressionnpx skills add Oriolshhh/runware-image-mcp --skill context-compressiongit clone --depth 1 https://github.com/Oriolshhh/runware-image-mcpWrote 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/oriolshhh/runware-image-mcp/context-compression)<a href="https://agentmods.dev/skills/oriolshhh/runware-image-mcp/context-compression"><img src="https://agentmods.dev/badge/skills/oriolshhh/runware-image-mcp/context-compression.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 | $0.00013 | $0.00374 |
| Opus 5 | $0.00006 | $0.00187 |
| Sonnet 5 | $0.00003 | $0.00075 |
| Haiku 4.5 | $0.00001 | $0.00037 |
Grade A, and why
context-compression 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 5d 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
Context Compression
Purpose
Reduce large logs, transcripts, and outputs to a compact summary that preserves every fact needed to continue the work.
When to use it
- Long tool output, test logs, or build logs.
- Handing off context near a context-window limit.
Instructions
- Preserve exact failures, commands, filenames, line numbers, and assertions.
- Preserve API changes, decisions, and open risks verbatim.
- Summarize repetitive or noisy passages; never drop a unique fact.
- Separate observed facts, inferences, and uncertainty.
- State explicitly what was omitted and why.
Output format
- Facts (observed, exact).
- Inferences (clearly labeled).
- Open / uncertain.
- Omitted (what was dropped and why).
Anti-patterns
- Paraphrasing an error message and losing its exact text.
- Presenting an inference as an observed fact.
- "Compressing" by deleting information that is still needed.
Verification checklist
- A new reader can identify the objective, current state, exact failures, decisions, constraints, modified files, verification results, and next action.
- Repeated material is collapsed, while every unique fact remains.
- Sensitive values are omitted or redacted without hiding that redaction occurred.
Apply
context-discoverybefore broad scanning: use a supplied context capsule first; otherwise check context frontmatter freshness, read.agent/context/routing.md, load only relevant summaries, and verify critical claims against source.
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.
- 5d ago First seen · 43 lines · 13 tokens per session scan A 199a1a2229ed
context-compression is a skill published in the GitHub repository Oriolshhh/runware-image-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 13 tokens to every session and 374 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.
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