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 gustavo-meilus/aiboarding --skill compress-onboardinggit clone --depth 1 https://github.com/gustavo-meilus/aiboardingWrote 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/gustavo-meilus/aiboarding/compress-onboarding)<a href="https://agentmods.dev/skills/gustavo-meilus/aiboarding/compress-onboarding"><img src="https://agentmods.dev/badge/skills/gustavo-meilus/aiboarding/compress-onboarding/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/gustavo-meilus/aiboarding/compress-onboarding"><img src="https://agentmods.dev/badge/skills/gustavo-meilus/aiboarding/compress-onboarding.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 | $0.00089 | $0.01524 |
| Opus 5 | $0.00044 | $0.00762 |
| Sonnet 5 | $0.00018 | $0.00305 |
| Haiku 4.5 | $0.00009 | $0.00152 |
Grade A, and why
compress-onboarding 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 8d 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compressing onboarding files
Instruction files load every session, so every saved token compounds. Compress prose aggressively while never touching the technical payload - and never trading away clarity where ambiguity is dangerous.
Announce at start: "Using compress-onboarding on at level ."
Usage: compress-onboarding <file> [--level off|lite|full|ultra]
Default file: the repo's AGENTS.md. Works under any SKILL.md-compatible runtime.
Levels (sticky per repo)
Resolve the level from --level if given, else .aiboarding/config.json: compression_level, else full. When --level is given, persist it back to
config.json - the level is a per-repo decision, not per-run.
off- no rewriting. Still run the size report (step 5) so bloat is visible.lite- remove filler, pleasantries, hedging, and restatement. Full sentences kept. ("In order to build the project, you should run…" → "To build, run…")full(default) - additionally drop articles, compress to fragments and short synonyms, allowX → Ynotation. ("The dev server can be started withnpm run dev" → "Dev server:npm run dev.")ultra- telegraphic; every non-load-bearing word goes. Use only when the effective instruction-chain audit needs it; confirm with the user before first use.
Byte-preservation invariants (hard guarantees)
Compression must NEVER alter: fenced code blocks (including the fence lines),
inline backtick spans, shell commands, URLs, file paths, identifiers and symbol
names, quoted error strings, <!-- aiboarding-* --> markers, YAML frontmatter, and
table structure. If a protected span is wrong, fixing it is an update, not a
compression - route it through update-agent-onboarding.
While rewriting, keep commands/identifiers/paths/error strings backtick-quoted (add backticks where the source lacks them - adding protection is allowed; removing it is not). The checker treats backtick spans as protected.
High-consequence preservation
Before rewriting, classify complete high-consequence regions. Preserve every
identified region verbatim, byte-for-byte, by default. full or ultra never
authorize rewriting one.
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.
- 8d ago First seen · 104 lines · 89 tokens per session scan A d3732f37e4a3
compress-onboarding is a skill published in the GitHub repository gustavo-meilus/aiboarding (2 stars, last pushed 11d ago), licensed MIT. It adds 89 tokens to every session and 1,524 once invoked, about $0.0004 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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