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 Bilal140202/the-lord-of-the-skills --skill can1357__oh-my-pigit clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skillsWrote 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/bilal140202/the-lord-of-the-skills/can1357__oh-my-pi)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/can1357__oh-my-pi"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/can1357__oh-my-pi/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/bilal140202/the-lord-of-the-skills/can1357__oh-my-pi"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/can1357__oh-my-pi.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 | $0.00068 | $0.00873 |
| Opus 5 | $0.00034 | $0.00436 |
| Sonnet 5 | $0.00014 | $0.00175 |
| Haiku 4.5 | $0.00007 | $0.00087 |
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 12d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Semantic Compression
LLMs reconstruct grammar from content words. Remove predictable glue; keep semantic payload. Prefer fragments over sentences.
Aggressive Stance
- Output can be noun/verb stacks, list fragments, or label:value phrases.
- Default to deletion; keep function words only when loss changes meaning.
- Prefer base verb forms; drop tense/aspect unless timeline is critical.
Deletion Tiers
Tier 1 — Always delete (even if fragments):
- Articles: a, an, the
- Copulas: is, are, was, were, am, be, been, being
- Expletive subjects: "There is/are...", "It is..."
- Complementizer: that (as clause marker)
- Pure intensifiers: very, quite, rather, really, extremely, somewhat
- Filler phrases: "in order to" → to, "due to the fact that" → because, "in terms of" → delete
- Infinitive "to" before verbs (unless it prevents noun/verb confusion)
- Conjunctions when list/contrast obvious: and, or, but
Tier 2 — Delete unless meaning changes:
- Auxiliary verbs: have/has/had, do/does/did, will/would (keep if tense/aspect matters)
- Modal verbs: can/could/may/might/should (keep when obligation/permission/possibility is critical; always keep must/must not)
- Pronouns: it/this/that/these/those/he/she/they (drop when referent obvious; replace with noun if ambiguous)
- Relative pronouns: which, that, who, whom
- Prepositions: of, for, to, in, on, at, by (keep for material, direction, agency, or disambiguation)
Tier 3 — Delete only if relation still clear:
- Remaining prepositions: with/without, between/among, within, after/before, over/under, through (drop only if relation obvious)
- Redundant adverbs: "shout loudly" → "shout"
Always Preserve
- Nouns, main verbs, meaning-bearing adjectives/adverbs
- Numbers, quantifiers: "at least 5", "approximately", "more than"
- Uncertainty markers: "appears", "seems", "reportedly", "what sounded like"
- Negation: not, no, never, without, none
- Temporal markers: dates, frequencies, durations
- Causality and conditionals: because, therefore, despite, although, if, unless
- Requirements/permissions: must, required, prohibited, allowed
- Proper nouns, titles, technical terms
- Prepositions encoding relationships: from/to (direction), with/without (inclusion), between/among/within (relation), after/before (temporal), by (agent if passive)
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.
- 12d ago First seen · 67 lines · 68 tokens per session scan A d71b1d40cac6
semantic-compression is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (4 stars, last pushed 6d ago), licensed MIT. It adds 68 tokens to every session and 873 once invoked, about $0.0003 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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