kochetkov-ma/claude-brewcodeMIT4 files

Text Optimizer

Optimizes text, prompts, and documentation for LLM token efficiency. Applies 52 research-backed rules across 8 categories: Claude behavior, token efficiency, structure, deduplication, reference integrity, perception, LLM comprehension, and aggressive lossy (deep only). Use when optimizing prompts, reducing tokens, compressing verbose docs, or improving LLM instruction quality.

Specification
Skill ID
kochetkov-ma/claude-brewcode/text-optimizer
Publisher
kochetkov-ma
Repository
claude-brewcode
Installs
0
Files
4
License
MIT
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

kochetkov-ma/claude-brewcode/text-optimizerInstalls these files
  • LICENSE
  • README.md
  • SKILL.md
  • references/rules-review.md

What this skill tells the agent

Plugin: kochetkov-ma/claude-brewcode

Text Optimizer

Reduces token count in prompts, docs, and agent instructions by 20–40% without losing meaning. Applies 52 research-backed rules across 8 categories: Claude behavior, token efficiency, structure, deduplication, reference integrity, perception, LLM comprehension, aggressive lossy (deep only).

Benefits: cheaper API calls · faster model responses · clearer LLM instructions · fewer hallucinations

Examples:

/text-optimize prompt.md          # single file, medium mode (default)
/text-optimize -d agents/         # deep mode — all .md files in directory
_Skill text is written for LLM consumption and optimized for token efficiency._

Text & File Optimizer

Step 0: Load Rules

REQUIRED: Read references/rules-review.md before ANY optimization. If file not found -> ERROR + STOP. Do not proceed without rules reference.

Modes

Parse $ARGUMENTS: -l/--light | -d/--deep | no flag -> medium (default).

ModeFlagScope
Light-l, --lightText cleanup only — structure, lists, flow untouched
Medium_(default)_Balanced restructuring — all standard transformations
Deep-d, --deepMax density — rephrase, merge, compress aggressively

Rule ID Quick Reference

CategoryRule IDsScope
Claude behaviorC.1-C.8Literal following, avoid "think", positive framing, match style, descriptive instructions, overengineering, avoid ALL-CAPS, prompt format
Token efficiencyT.1-T.8, T.10Tables, bullets, one-liners, inline code, abbreviations, filler, comma lists, arrows, strip whitespace
StructureS.1-S.8XML tags, imperative, single source, context/motivation, blockquotes, progressive disclosure, consistent terminology, ref depth
DeduplicationD.1-D.6Exact/near/cross-format merge, emphasis cap <=2, cross-file SSOT, wrong-merge guard
Reference integrityR.1-R.3Verify file paths, check URLs, linearize circular refs
PerceptionP.1-P.6Examples near rules, hierarchy, bold keywords, standard symbols, instruction order, default over options
LLM ComprehensionL.1-L.8Critical info position, documents-first, conciseness, quote-first, add WHY, reiterate constraint, prompt repetition, preserve scope qualifiers
Aggressive lossy (deep only)A.1-A.4Line fusion, low-value word drop, aggressive paraphrase, common-knowledge elision

ID-to-Rule Mapping

IDRuleIDRule
C.1Literal instruction followingC.2Avoid "think" word
C.3Positive framing (do Y not don't X)C.4Match prompt style to output
C.5Descriptive over emphatic instructionsC.6Overengineering prevention
T.1Tables over prose (multi-column)T.2Bullets over numbered (~5-10%)
T.3One-liners for rulesT.4Inline code over blocks
T.5Standard abbreviations (tables only)T.6Remove filler words
T.7Comma-separated inline listsT.8Arrows for flow notation
S.1XML tags for sectionsS.2Imperative form
S.3Single source of truthS.4Add context/motivation
S.5Blockquotes for criticalS.6Progressive disclosure
R.1Verify file pathsR.2Check URLs
R.3Linearize circular refsP.1Examples near rules
P.2Hierarchy via headers (max 3-4)P.3Bold for keywords (max 2-3/100 lines)
P.4Standard symbols (→ + / ✅❌⚠️)
S.7Consistent terminologyS.8One-level reference depth
P.5Instruction order (anchoring)P.6Default over options
C.7Avoid ALL-CAPS emphasis (4.x)C.8Prompt format → output format
T.10Strip whitespace from code
L.1Critical info at START or ENDL.2Documents first, query last
L.3Explicitly request concisenessL.4Quote-first grounding
L.5Add WHY to instructionsL.6Reiterate constraint at END
L.7Prompt repetition (non-reasoning)L.8Preserve scope qualifiers
D.1Exact-duplicate mergeD.2Near-duplicate merge (keep specific)
D.3Cross-format duplicateD.4Emphasis cap (<=2/doc, echo @ END)
D.5Cross-file dedup (SSOT + pointer)D.6Wrong-merge guard
A.1Line fusion (loss-free merge)A.2Low-value word drop (gate-neutral)
A.3Aggressive paraphrase (preserved)A.4Common-knowledge elision (ledger)

Mode-to-Rules Mapping

ModeAppliesNotes
LightC.1-C.8, T.6, D.1, R.1-R.3, P.1-P.4, L.1-L.8Text cleanup only — no restructuring
MediumAll rules (C + T + S + D + R + P + L)Balanced transformations
DeepAll rules (C + T + S + D + R + P + L) + A.1-A.4 (aggressive lossy)Merge sections, max compression

Loss Budget per Mode

Content essence is untouchable at light/medium; small deliberate loss only at deep — explicitly reported. Dedup-merged facts count as preserved, never as loss.

ModeSemantic match targetAllowed loss
Light100%None — wording cleanup only
Medium100%None — self-check fact inventory, zero loss
Deep>= 95%Low-value connective detail; self-verify round required, warn with loss list if < 95%

Deduplication Pass (All Modes)

Runs during analysis, BEFORE compression:

  1. Build fact inventory: one atomic fact per line, numbered
  2. Flag facts appearing 2+ times (exact, reworded, or cross-format)
  3. Classify each repeat: intentional emphasis (marked critical/blockquote, or start+end sandwich) vs accidental
  4. Accidental -> merge to single MOST SPECIFIC statement (D.1-D.3), best position wins
  5. Intentional -> cap at 2: full form early + <=1-line echo at END (D.4)
  6. Wrong-merge guard (D.6): differing scope/numbers/conditions = NOT duplicates — keep both

Usage

InputAction
No argsPrompt user for file or folder path
Single pathProcess file directly
path1, path2Process files sequentially
-l file.mdLight mode — text cleanup only
-d file.mdDeep mode — max compression
folder/All .md files in directory

File Processing

Input Parsing

InputAction
No argsPrompt user for file or folder path
Single pathProcess directly
path1, path2Process files sequentially

Execution Flow

  1. Read references/rules-review.md — load all optimization rules
  2. Read target file(s)
  3. Analyze: identify type (prompt, docs, agent, skill), note critical info and cross-references

3a. Dedup pass (D.1-D.6): fact inventory -> merge accidental dups -> cap intentional emphasis at 2/doc 3b. Deep only: aggressive lossy pass (A.1 fusion -> A.3 paraphrase -> A.2 word drop -> A.4 elision); A.2/A.4 drops -> loss ledger; A.4 counts as elided-known against the >=95% gate, A.2 is gate-neutral

  1. Apply rules by mode (see Mode-to-Rules Mapping)
  2. Edit file with optimized content

5a. Medium: self-check — re-check fact inventory against output, zero loss required 5b. Deep mode: self-verify — fact inventory original vs compressed, (kept + merged)/total >= 95%; merged = preserved; warn with loss list if below

  1. Generate optimization report

Quality Checklist

Before

  • [ ] Read entire text
  • [ ] Identify type (prompt, docs, agent, skill)
  • [ ] Note critical info and cross-references

During — Apply by Mode

CheckLightMedDeep
C.1-C.8 (Claude behavior)YesYesYes
T.6 (filler removal)YesYesYes
T.1-T.5, T.7-T.8 (token compression)-YesYes
T.10 (strip code whitespace)-YesYes
S.1-S.8 (structure/clarity)-YesYes
D.1 (exact dedup)YesYesYes
D.2-D.4, D.6 (smart dedup + emphasis cap)-YesYes

Use this skill in a project

Open any RiverX project, search the Skills panel for kochetkov-ma/claude-brewcode/text-optimizer, and install it in one click.

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