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 nweii/agent-stuff --skill semantic-compressiongit clone --depth 1 https://github.com/nweii/agent-stuffWrote 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/nweii/agent-stuff/semantic-compression)<a href="https://agentmods.dev/skills/nweii/agent-stuff/semantic-compression"><img src="https://agentmods.dev/badge/skills/nweii/agent-stuff/semantic-compression/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/nweii/agent-stuff/semantic-compression"><img src="https://agentmods.dev/badge/skills/nweii/agent-stuff/semantic-compression.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 | $0.00056 | $0.01203 |
| Opus 5.5 | $0.00022 | $0.00481 |
| Sonnet 5.5 | $0.00011 | $0.00241 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
semantic-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 26d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Semantic compression
Find the smallest expression that carries the meaning the user needs. Compression may produce a tighter explanation, a vivid phrase, one concrete word, an established term, or a coined expression. Success means preserving the distinctions, implications, and texture that matter in context.
Process
1. Establish the semantic payload
Read the surrounding conversation, source material, and writing guidelines before asking questions. Identify:
- what the expression must literally mean
- what it should imply without stating outright
- its emotional texture and degree of force
- the relationships it must preserve, such as direction, causality, reciprocity, or recursion
- its audience, register, and role in the larger passage
- any distinctions that nearby words or concepts already carry
Determine whether the source and request support one semantic payload or several. When faithful alternatives depend on the user's unstated priority, taste, or point of view, show the alternatives and what each would preserve or lose, then ask what must survive. If the user delegates the choice, state the assumption you will use.
Infer only what the available context supports. If a missing detail could materially change the result, ask one specific question at a time until the required payload is clear. Do not ask the user to repeat context already available.
This step is complete when you can state what the compressed expression must preserve and what it may discard, and any selection judgment has been supplied or explicitly delegated.
2. Separate meaning from wording
Restate the payload internally without borrowing the source construction. Identify accidental bulk: modifiers compensating for a weak noun or verb, repeated implications, abstractions hiding a concrete action, qualifications that no longer change the claim, or several adjacent words pointing at one available concept. Look for a word whose ordinary associations absorb the work of a modifier or explanation.
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.
- 26d ago Changed · +2 lines 01d1b4e19bad
- 1mo ago First seen · 109 lines · 56 tokens per session scan A ca0182f2e50b
semantic-compression is a skill published in the GitHub repository nweii/agent-stuff (10 stars, last pushed 3d ago), licensed MIT. It adds 56 tokens to every session and 1,203 once invoked, about $0.0002 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.
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