condense
Maximize information density: preserve all instructions, remove prose filler.
Install
npx skills add https://github.com/notque/vexjoy-agent/tree/main/skills/code-quality/condense
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install notque-vexjoy-agent@llmmart
git clone https://github.com/notque/vexjoy-agent.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole notque/vexjoy-agent collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
Condense
Strip prose filler from .md files. Preserve every instruction. This skill practices what it preaches.
Phase 1: SCOPE
Identify targets.
- Single file: User names a path. Read it.
- Glob: User gives a pattern (
agents/*.md). Expand, list matches, confirm with user. - Batch (10+ files): Dispatch parallel agents, one per file.
Mechanical pre-pass (deterministic, run before LLM condensing): strip trailing whitespace and consecutive blank lines that inflate Opus token counts. The script handles the mechanical reduction so the LLM phase focuses on prose density.
python3 scripts/check-whitespace.py --fix <target-file-or-dir> # 0=clean, 1=violations fixed
Run on the scoped targets (defaults to agents/**/*.md and skills/**/*.md when no path given). Then proceed to the LLM pass on the same files.
Gate: At least one target file identified and readable; mechanical pre-pass run.
Phase 2: CONDENSE
For each file:
- Read the full file. Record word count.
- Rewrite in place applying the rules below.
- Record new word count.
Rules
KEEP (never cut):
- Every instruction, rule, gate, phase, step
- Tables, code blocks, commands, paths
- YAML frontmatter (do not alter)
- Structure: headers, numbered lists, phase ordering
- Technical terms naming specific things
- Reference loading tables
- Error handling sections
- Non-obvious "because X" reasoning
CUT:
- Redundant restatements of the same rule
- "Because X" on obvious rules
- Motivational framing ("this will help you", "it is important to note")
- Filler phrases: "in order to", "it should be noted that", "it is worth mentioning"
- Examples that repeat what the phase already says
- Paragraphs saying the same thing from different angles -- merge to one
STYLE: Short sentences. Active voice. Concrete words. If you can cut a word without losing an instruction, cut it.
DELETE TEST
Before cutting any sentence: "If I remove this, does the reader lose an instruction, rule, or decision?" No = cut. Yes = keep.
Boundaries
Do not reorganize sections, change meaning, add ideas, alter paths/commands, drop tables or code blocks, or modify YAML frontmatter values.
Phase 3: VERIFY
For each condensed file:
- YAML check: Confirm frontmatter parses.
python3 -c "import yaml; yaml.safe_load(open('<file>').read().split('---')[1])" - Report: Show
| File | Before | After | Reduction |table with word counts. - Instruction check: Grep original for key terms (phase names, gate names, commands). Confirm each appears in condensed version. If any missing, restore from original.
Gate: YAML parses. No instructions lost. Reduction reported.
Error Handling
No prose to cut: Report 0% reduction, move to next file.
Instruction removed: Re-read original, restore missing instruction, re-verify.
YAML broken: Restore original frontmatter verbatim, re-condense body only.
Non-.md file: Skip with warning.
Files (vexjoy-agent)
-
SKILL.md 3.6 KB
--- name: condense description: "Maximize information density: preserve all instructions, remove prose filler." user-invocable: true # justification: users type "/condense <file>" directly to tighten # specific files; /do dispatch adds unnecessary routing overhead # for a targeted file-editing operation. argument-hint: "<file-or-glob>" allowed-tools: - Read - Edit - Write - Bash - Grep - Glob routing: triggers: - condense - reduce words - clarity pass - information density - remove prose - tighten - fewer words pairs_with: - toolkit complexity: Simple category: code-quality --- # Condense Strip prose filler from .md files. Preserve every instruction. This skill practices what it preaches. ## Phase 1: SCOPE Identify targets. 1. **Single file**: User names a path. Read it. 2. **Glob**: User gives a pattern (`agents/*.md`). Expand, list matches, confirm with user. 3. **Batch (10+ files)**: Dispatch parallel agents, one per file. **Mechanical pre-pass** (deterministic, run before LLM condensing): strip trailing whitespace and consecutive blank lines that inflate Opus token counts. The script handles the mechanical reduction so the LLM phase focuses on prose density. ```bash python3 scripts/check-whitespace.py --fix <target-file-or-dir> # 0=clean, 1=violations fixed ``` Run on the scoped targets (defaults to `agents/**/*.md` and `skills/**/*.md` when no path given). Then proceed to the LLM pass on the same files. **Gate**: At least one target file identified and readable; mechanical pre-pass run. --- ## Phase 2: CONDENSE For each file: 1. Read the full file. Record word count. 2. Rewrite in place applying the rules below. 3. Record new word count. ### Rules **KEEP** (never cut): - Every instruction, rule, gate, phase, step - Tables, code blocks, commands, paths - YAML frontmatter (do not alter) - Structure: headers, numbered lists, phase ordering - Technical terms naming specific things - Reference loading tables - Error handling sections - Non-obvious "because X" reasoning **CUT**: - Redundant restatements of the same rule - "Because X" on obvious rules - Motivational framing ("this will help you", "it is important to note") - Filler phrases: "in order to", "it should be noted that", "it is worth mentioning" - Examples that repeat what the phase already says - Paragraphs saying the same thing from different angles -- merge to one **STYLE**: Short sentences. Active voice. Concrete words. If you can cut a word without losing an instruction, cut it. ### DELETE TEST Before cutting any sentence: "If I remove this, does the reader lose an instruction, rule, or decision?" No = cut. Yes = keep. ### Boundaries Do not reorganize sections, change meaning, add ideas, alter paths/commands, drop tables or code blocks, or modify YAML frontmatter values. --- ## Phase 3: VERIFY For each condensed file: 1. **YAML check**: Confirm frontmatter parses. ```bash python3 -c "import yaml; yaml.safe_load(open('<file>').read().split('---')[1])" ``` 2. **Report**: Show `| File | Before | After | Reduction |` table with word counts. 3. **Instruction check**: Grep original for key terms (phase names, gate names, commands). Confirm each appears in condensed version. If any missing, restore from original. **Gate**: YAML parses. No instructions lost. Reduction reported. --- ## Error Handling **No prose to cut**: Report 0% reduction, move to next file. **Instruction removed**: Re-read original, restore missing instruction, re-verify. **YAML broken**: Restore original frontmatter verbatim, re-condense body only. **Non-.md file**: Skip with warning.
Comments (0)
Sign in to join the conversation.
Reviews (0)
No reviews yet.
No comments yet.