version: "1.0.1" name: semantic-compression description: Re-encode verbose prose into a dense telegraphic register — punctuation as connectives, label frames, verbless assertions — without losing normativity or precision. Use when compressing system prompts, tool/function descriptions, skill bodies, or agent instructions; reducing token count or context bloat; making documentation token-efficient for LLM input; or rewriting text in compressed notation.

Semantic Compression

Compression is re-encoding, not word deletion. Filtering function words out of an English sentence leaves a damaged English sentence (System design: efficient process incoming data, multiple sources). Instead re-frame each claim in a register whose grammar is punctuation and layout — then the function words have no work left and drop out on their own.

Target texts are load-bearing: tool descriptions, system prompts, skills. A model executes them cold, with no author present to disambiguate. Compression that forces a guess is a bug, not a saving.

Procedure

1. Density gate — check before touching anything. Two signals, in order: (a) are articles and copulas already near-absent? (b) compress one representative section and measure the token delta. Already in this register (house-style prompt, tool doc, spec) or delta under ~10%? STOP. Report that it is already dense and keep the original. Bullet length alone is a weak signal — API literals and enumerations inflate it. Measured on a real house-style tool prompt: 853 → 778 tokens (8.8%), while that pass silently dropped a NEVER assume … rule, a throw condition, and a full-res detail. On already-dense text the remaining words are the payload, and the expected saving is smaller than the expected loss.
2. Split the source into atomic claims: one definition, obligation, default, or fact each.
3. Inventory the payload first, before deleting anything. List every load-bearing token: identifiers, error/exception names, throw conditions, defaults with their units, bounds, and every MUST/NEVER/PREFER line. Anything you then drop is a loss you declare deliberately rather than discover later.
4. Cut what the model already knows. "JSON is a text format", "tests catch regressions" → delete. Keep only what is specific to this tool, repo, or domain.
5. Cut restatements. Merge every duplicate of one rule into a single canonical line, placed where it is needed. Two statements of one rule with different scope are not duplicates.
6. Frame each claim — definition · obligation · default · condition→consequence · enumeration · verdict. The frame picks the construction.
7. Hoist repeated qualifiers into one scope line: three mentions of "relative to the repo root" → All paths repo-relative. once, up top.
8. Re-encode, then run Verification.

Frames

Constructions behind them:

• Verbless assertion — X true / X false / X required / X unsupported. Copula deleted; the predicate carries.
• Label frame — X: value for "the X is / means / consists of". One colon per line, never nested.
• Subject elision across a run — name the subject once, chain bare predicates: Integer since …; positive since …; unique.
• Asyndeton — parallel items, no conjunction: articles, copulas, expletives.
• Scope declaration — one line retypes everything after it: All paths repo-relative. · Times in ms. · All congruences mod 4.
• Lazy specification — state only enough to decide: 3·13·34-1 big (over the bound; exact value irrelevant). Name the bound somewhere the reader can see it.
• Metonymy — an object stands for the proposition about it: y=z implies (1,1,1). Only where exactly one reading exists.

Operators

Punctuation carries the connective:

• : — announce, name, define ("is", "means", "the following")
• → — yields, produces, becomes ("which results in")
• ⇒ — therefore, concludes
• — — gloss, or "therefore"
• / — equivalently, i.e.
• ; — next step, same topic ("Then,", "After that,")
• , — inference chain ("and so")
• ≠ — neither/nor, distributed over a list
• ✓ — verified, obligation discharged
• > — precedence ("arg > env > default")
• | — alternatives within an enum ("open | close | run")

Ambiguity is the only disqualifier, never unfamiliarity. Where a glyph takes a second reading in its slot — — as a parenthetical dash, / as a path separator or "per", , as a list comma — write the word instead.

Symbols do not save tokens; structure does. Measured (cl100k_base; Claude's tokenizer differs, but BPE arity for rare glyphs is similar): → ⇒ ≤ · ✓ cost 1 token each, ≡ costs 2, -> costs 2, and gives costs 1. So a one-for-one word→glyph swap saves nothing and costs clarity. Substitute a glyph only where it eats a multi-word phrase. Superscripts do pay: x²+y² = 4 tokens, x^2+y^2 = 6.

Never invent private glyphs — a bespoke one needs a legend that costs more than it saves.

Deletion

Always delete: articles; copulas (is/are/was/be/been); expletive there/it; complementizer that; relative pronouns; intensifiers (very, quite, really, extremely); filler ("in order to"→to, "due to the fact that"→because, "it is important to note that"→∅, "in terms of"→∅); politeness ("please", "feel free to"); hedged framing ("you may want to consider").

Delete unless load-bearing: auxiliaries (have/do/will); pronouns with an obvious referent; prepositions of/for/to/in/on/at/by; conjunctions where the list is obvious; adverbs already implied by the verb ("shout loudly").

Never delete — this is the payload:

• Normative modals: MUST, NEVER, SHOULD, MAY. The RFC 2119 word is the instruction.
• Negation and exception: not, no, never, without, none, except, unless.
• Numbers, units, bounds, quantifiers: "at least 5", "≤100", "max 1 MiB", "1-indexed".
• Conditionals and causality: if, unless, because, since, so.
• True hedges: "approximately", "usually", "appears" — deleting one asserts certainty the source did not have.
• Exact strings: identifiers, API names, flags, paths, regexes, format literals, error text.
• Examples that demonstrate a shape. Compressing an example destroys the thing it demonstrates.
• Prepositions where the relation flips meaning: "read from X" ≠ "read to X".
• Throw/failure conditions, and warnings about silent failure ("never assume it landed because no error appeared"). They read like padding and are behavioral.
• Scar tissue: a line that exists because someone already made that mistake. It looks redundant because it now prevents the error. git blame before cutting anything that looks obvious.

Private register — never ship

The scratchpad style that generates this register carries features that work only while writer and reader are the same person, minutes apart. Strip all of them:

• External deixis — A, B, C, G, "the equation", "the claim above". Shipped text is self-contained: name the thing.
• Scratchpad residue — Hmm, Actually, Wait, just, fine, Good; goals revised mid-line; abandoned clauses.
• Layered corrections — a wrong value left standing beside its fix. A cold reader cannot tell which pass won. Delete the loser.
• Dead branches — an abandoned approach left beside the chosen one. A model may execute the abandoned one.
• Ambiguous `...` and `?` — in notes they mean omitted / abandoned / infinite, and conjecture / check-this. In shipped text they mean nothing. Drop both.
• Nested colons — Step: from X: cases: a,b=1: 3-c: is unparseable cold. One colon per line.
• Unmarked instruction vs data — a bare line like Word limit 1200 - write concisely sitting in content is indistinguishable from content. Keep instructions in a marked channel: heading, tag, or MUST line.
• Revisiting instead of rewriting — fine while thinking, fatal in a prompt. One canonical statement per rule.

Tool and skill descriptions

The body compresses hard. The trigger does not.

• A tool's or skill's description field is retrieval surface, not documentation: it is matched against the user's own phrasing. Keep natural, keyword-redundant alternatives ("compress prompt", "reduce token count", "token-efficient") even though a reader needs only one. Compress the body; NEVER compress the trigger.
• Params — drop type, enum, or default from the prose ONLY when the wire schema the model actually sees exposes it, and (if you ran the tool-prompt-optimization probe) the probe recovered it from schema alone. Otherwise keep it. Defaults are the trap: wire schemas frequently omit default entirely, and even when present it carries no direction or semantics — gitignore: true does not say "respects gitignore" — which is why tool-prompt-optimization classes defaults-and-their-direction as content no model recovers. Absent that evidence, preserve the default, its unit, and any precedence rule (arg > env > default). Prose always keeps what no schema can express: interaction, precedence, failure mode.
• Imperative for actions (open before run); label frames for facts (Default 30s.).
• Scope split — this skill owns the re-encoding mechanics only. What belongs in a tool prompt at all (anatomy, surface-not-machinery, what stays out) → tool-prompt-optimization, which also measures schema/prose overlap before you cut. House style (tag vocabulary, RFC 2119 keywords, positioning) → system-prompts. Compress after those two have decided what ships.

Worked example

Source (55 words, 63 tok):

The timeout parameter controls how long the tool will wait for the process to become ready. If you do not provide a value, it defaults to 30 seconds. Note that if you have specified both a log pattern and a port, then both of these conditions must be satisfied before the process is considered ready.

Compressed (14 words, 20 tok):

Readiness timeout: default 30s. Log pattern + port both supplied ⇒ BOTH must pass.

Rejected as over-compressed — timeout 30 log+port both: loses the unit, loses that 30 is a default rather than a fixed value, loses the obligation, and leaves both dangling.

Verification

1. Declare every loss, then judge the draft against that list. Name each dropped claim, qualifier, default, example, or exact string, and why the text is still correct without it. A declared loss is a decision a reader can audit; an undeclared one is a silent regression. Review with the list in front of you, not from memory of what you intended.
2. Ambiguity scan. For every : → — /: can a reader assign a second reading? Fix it. Watch for ambiguity the source did not have — a dropped receiver (.ref("e5") on what?), a singular silently pluralized ("previous snapshot" → "previous generations").
3. Measure the pair with the target tokenizer. Word counts and function-word rates do not predict token savings. Expect no fixed ratio — measured on real pairs (cl100k): a verbose doc paragraph 63 → 20 tok, a verbose prose section 360 → 222 tok, an already-dense house-style tool prompt 853 → 778 tok. Under ~10% is the signal to stop, revert, and keep the original.
4. Stop rule. Stop deleting when the next deletion makes the reader guess. Correctness beats ratio, always.

Running it as a command

omp compress <file> drives exactly this loop with two tools and nothing else.

Its session is isolated on purpose, because the input is itself a prompt: the default system prompt is replaced (not appended to), and skill, rule, AGENTS.md, prompt-template, and slash-command discovery are all passed empty — every one of those defaults to ON when omitted, and each would inject instruction-shaped project text into a job whose only legitimate input is the document. Audited on a live session: one system-prompt part, tools rewrite, approve, no AGENTS.md or rule content present.

The source is quoted inside a nonce-delimited block and declared inert, so MUST/NEVER lines in the document get compressed rather than obeyed — verified with a document whose first paragraph ordered the compressor to emit OK and skip the rest: it compressed the real content and declared the injected paragraph as a deliberate loss.

• rewrite submits the full compressed text plus every declared loss.
• The command answers with the draft, its measured word/token delta, and that loss list, then asks for a verdict.
• approve accepts the reviewed draft. Approval before a review turn is rejected, and a new draft voids an earlier approval.
• Only an approved draft is written: -o <path>, -i in place, otherwise stdout (the report goes to stderr, so > out.md captures just the text). -r bounds the drafts; an unapproved run writes nothing and exits 1.

The runtime contract it hands the agent lives in packages/coding-agent/src/compress/prompts/system.md. It is the operative subset of this file; when they disagree, this file wins and the prompt gets fixed.