agentsclimarketplace

Reinjected attachment pruning before summary

Skill vishuwa2004/cskill-agents/agents/codex/skills/reinjected-attachment-pruning-before-summary

Build curated agent skills for coding CLIs, terminal tools, context engines, remote bridges, and multi-agent runtimes

Install
npx -y skills add vishuwa2004/cskill-agents --skill reinjected-attachment-pruning-before-summary

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Drop attachment classes that will be regenerated after compaction so the summarizer spends tokens on lasting context instead of disposable payloads.

SKILL.md

1.6 KB, 246 tokens by cl100k_base, as published. Nobody here has run it

SKILL: Reinjected Attachment Pruning Before Summary

Domain: context-management Trigger: Use when some attachment types are guaranteed to be regenerated after compaction and should not consume summary budget. Source Pattern: Distilled from reviewed reinjected-attachment pruning strategies.

Core Method

Remove only the attachment classes that the system already knows it will regenerate after compaction. This keeps the summary focused on durable conversational state and avoids paying twice for transient discovery or guidance payloads. Prune before normalization and summary generation so the saved budget reduces the compaction request itself.

Key Rules

  • Prune only attachment classes with a known reinjection path.
  • Apply pruning before summary generation, not after.
  • Keep the pruning contract explicit so future attachment types are not stripped accidentally.

Example Application

If skill discovery attachments are recreated on the next turn after compaction, strip them before summary generation so the compactor focuses on the real debugging conversation.

Anti-Patterns (What NOT to do)

  • Do not strip attachments that lack a reinjection path.
  • Do not summarize large disposable attachments that will be reattached immediately afterward.
  • Do not use pruning as a blanket excuse to hide important durable state.

Gives 0 of the 12 instructions most note taking skills give in 246 tokens

Counted across 686 of the 876 authors here whose files we hold, read 2026-08-06

  • include a visual element on every slidein 44 of 686, across 13 files
  • use wikilinks for internal vault linksin 35 of 686, across 11 files
  • commit to a single visual motif across every slidein 34 of 686, across 9 files
  • read pptxgenjs guide before creating presentations from scratchin 30 of 686, across 6 files
  • keep 0.5 inch minimum marginsin 30 of 686, across 7 files
  • use subagents to visually inspect rendered slidesin 30 of 686, across 6 files
  • re-verify affected slides after every fixin 27 of 686, across 5 files
  • run content QA checks before declaring successin 26 of 686, across 3 files
  • Use Markdown links for external URLs onlyin 26 of 686, across 10 files
  • pick a bold topic specific color palettein 24 of 686, across 2 files
  • read editing guide before editing existing presentationsin 23 of 686, across 1 file
  • use one dominant color across all slidesin 23 of 686, across 1 file

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.