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Condense Agent Skill

Maximize information density: preserve all instructions, remove prose filler.

930 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
413
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/notque/vexjoy-agent --skill condense

The instruction itself

8 sections, as written by the author

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.

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How to use it

Copy the folder

Take notque/condense from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.