Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

Back to skills

Compile Knowledge

ASecurity

Compile durable knowledge into interlinked-markdown stores the "karpathy method" way — atomic files, [[wiki-links]], a maintained index. Use after producing research, intel, a digest, a learned non-obvious fact, or finishing any knowledge-shaped task, BEFORE you close it. Also when asked to "save this", "write this to the wiki", "update the wiki/memory", "log this finding", "structure this knowledge", or "follow the karpathy method".

207 stars
0 votes
0 copies
2 views
Added 9/4/2026
ai-agentsgogit

Security Analysis

A100/100

Scanned 9/4/2026

Install to Claude Code

$npx -y skills add NeverSight/skills_feed --skill compile-knowledge --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Compile Knowledge?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Compile Knowledge
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/neversight-compile-knowledge/badge)](https://www.skillsdirectory.com/skills/neversight-compile-knowledge)

More formats (shields.io, HTML) on the badges page.

Download Zip
Files
SKILL.md
---
name: compile-knowledge
description: >-
  Compile durable knowledge into interlinked-markdown stores the "karpathy
  method" way — atomic files, [[wiki-links]], a maintained index. Use after
  producing research, intel, a digest, a learned non-obvious fact, or finishing
  any knowledge-shaped task, BEFORE you close it. Also when asked to "save this",
  "write this to the wiki", "update the wiki/memory", "log this finding",
  "structure this knowledge", or "follow the karpathy method".
---

# compile-knowledge

Durable knowledge is worth keeping as many small, interlinked markdown files,
compiled over time and surfaced through an index — not as one giant doc, a chat
log, or a one-off file that rots. This skill makes compiling consistent so your
agent gets smarter over time instead of relearning the same things.

## Where it goes — pick the right store

- **Agent memory** (default, always available): your `.claude/.../memory/`
  folder with `MEMORY.md` as the index. This is the per-agent store and it
  survives restarts — it's the karpathy "external memory" that keeps you sharp
  across sessions. Governed by the memory rules already in your system prompt —
  follow them. For most agents this is the only store you need.
- **Shared wiki** (only if you work as a team): a `wiki/` folder in your project
  with a `wiki/index.md`. For knowledge the *whole team* benefits from — domain
  facts, research findings, reference material multiple agents would re-derive.
  Skip this entirely if you're a solo agent; don't manufacture team ceremony.

Rule of thumb: "only I act on this" → memory. "Anyone on my team might need
this" → shared wiki. Cross-link between them with `[[slug]]` when they relate.

## Before you write — the hygiene gate

Compile ONLY a durable, non-obvious fact. Skip and move on if it is:
- routine / derivable from the repo, git history, or existing docs,
- true only for this one conversation,
- already covered by an existing file (→ UPDATE that file instead, don't duplicate).

Most tasks (a deploy, a restart, a one-line fix) produce nothing durable. That is
fine — do not manufacture a memory to "have written something." Filler is worse
than nothing; it pollutes recall.

## The procedure

1. **Search first.** Look for an existing file on this topic (grep the store +
   skim the index). If one exists, edit it — never create a near-duplicate.
2. **Atomic.** One fact / one topic per file. If you're tempted to add a second
   unrelated fact, that's a second file.
3. **Name it.** kebab-case slug, with a type prefix for memory
   (`feedback_…`, `project_…`, `reference_…`, `user_…`) or a clear topic slug for
   the wiki. The slug is the link target.
4. **Frontmatter.** `name` (= the slug), `description` (ONE line — this is what
   gets matched during recall, make it specific), and a `type`/category.
5. **Body.** State the fact plainly. Link related entries with `[[slug]]` —
   liberally; a link to a file that doesn't exist yet is a fine TODO marker. For
   `feedback`/`project`, follow with **Why:** and **How to apply:** lines.
6. **Index.** Add or update a ONE-LINE pointer in the index (`MEMORY.md` for
   memory; `wiki/index.md` for the wiki): `- [Title](slug.md) — hook`. Keep it
   under ~200 chars; detail lives in the file, never the index. **If the wiki
   `index.md` doesn't exist yet, create it** so the store stays discoverable.
7. **Hygiene.** Delete files that turned out wrong. Convert relative dates to
   absolute. If the index is getting long, tighten lines — don't let it bloat.

## Anti-patterns

- A wall-of-text doc instead of atomic files.
- Research left as a standalone `notes.md` that never gets folded in — that's
  working notes, not knowledge. Compile the durable parts into the store.
- Duplicating a fact across memory AND wiki — pick one home, cross-link.
- Index entries that restate the whole file.
- Writing filler to satisfy a habit/checklist.

## Quick checklist

`[ ] durable & non-obvious? [ ] right store? [ ] updated existing vs new?`
`[ ] atomic + named + frontmatter? [ ] [[links]]? [ ] index line added?`

Attribution

NeverSightNeverSight
View sourceMore from NeverSight →
SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Related Skills

Caveman

Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.

1023331 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

686011 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3331 votes

catchup

Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.

611 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →