Agent skill

Knowledge Ops

by affaan-m in affaan-m/ECC

Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos).

MITAuto-check passedKnowledge Management

Install Knowledge Ops

skills CLI
$ npx skills add affaan-m/ECC --skill knowledge-ops -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC knowledge-ops --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/knowledge-ops .claude/skills/knowledge-ops && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
knowledge-ops
GitHub stars
276k
Used in
2 other repos
Token cost
~1.7k tokens
SKILL.md length
764 words
Files
1
Skills in repo
673
Repo updated
First seen
Licence
MIT

At a glance

Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos).

  • Works in 4 steps: Classify → Deduplicate → Store → …
  • The user wants to save
  • SKILL.md covers When to Activate, Knowledge Architecture, Ingestion Workflow and Sync Operations, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Knowledge Ops is an agent skill from affaan-m/ECC. Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Knowledge Management, covering Knowledge bases and Vector databases. It works with Model Context Protocol, Git and GitHub. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • The user wants to save
  • Search across their knowledge systems

Example prompts

  • “/knowledge-ops”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Classify
  2. Deduplicate
  3. Store
  4. Index

What it can do on your machine

Read from SKILL.md and the folder at commit ef648e0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Knowledge Ops loads about 1.7k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 764 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit ef648e0, republished under its MIT licence (© affaan-m). 764 words, ~1,688 tokens.

Download SKILL.mdSave it as .claude/skills/knowledge-ops/SKILL.md (or your agent's skills folder).
name
knowledge-ops
description
Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.
metadata.origin
ECC

Knowledge Operations

Manage a multi-layered knowledge system for ingesting, organizing, syncing, and retrieving knowledge across multiple stores.

Prefer the live workspace model:

  • code work lives in the real cloned repos
  • active execution context lives in GitHub, Linear, and repo-local working-context files
  • broader human-facing notes can live in a non-repo context/archive folder
  • durable cross-machine memory belongs in the knowledge base, not in a shadow repo workspace

When to Activate

  • User wants to save information to their knowledge base
  • Ingesting documents, conversations, or data into structured storage
  • Syncing knowledge across systems (local files, MCP memory, Supabase, Git repos)
  • Deduplicating or organizing existing knowledge
  • User says "save this to KB", "sync knowledge", "what do I know about X", "ingest this", "update the knowledge base"
  • Any knowledge management task beyond simple memory recall

Knowledge Architecture

Layer 1: Active execution truth
  • Sources: GitHub issues, PRs, discussions, release notes, Linear issues/projects/docs
  • Use for: the current operational state of the work
  • Rule: if something affects an active engineering plan, roadmap, rollout, or release, prefer putting it here first
Layer 2: Claude Code Memory (Quick Access)
  • Path: ~/.claude/projects/*/memory/
  • Format: Markdown files with frontmatter
  • Types: user preferences, feedback, project context, reference
  • Use for: quick-access context that persists across conversations
  • Automatically loaded at session start
Layer 3: MCP Memory Server (Structured Knowledge Graph)
  • Access: MCP memory tools (create_entities, create_relations, add_observations, search_nodes)
  • Use for: Semantic search across all stored memories, relationship mapping
  • Cross-session persistence with queryable graph structure
Layer 4: Knowledge base repo / durable document store
  • Use for: curated durable notes, session exports, synthesized research, operator memory, long-form docs
  • Rule: this is the preferred durable store for cross-machine context when the content is not repo-owned code
Layer 5: External Data Store (Supabase, PostgreSQL, etc.)
  • Use for: Structured data, large document storage, full-text search
  • Good for: Documents too large for memory files, data needing SQL queries
Layer 6: Local context/archive folder
  • Use for: human-facing notes, archived gameplans, local media organization, temporary non-code docs
  • Rule: writable for information storage, but not a shadow code workspace
  • Do not use for: active code changes or repo truth that should live upstream

Ingestion Workflow

When new knowledge needs to be captured:

1. Classify

What type of knowledge is it?

  • Business decision -> memory file (project type) + MCP memory
  • Active roadmap / release / implementation state -> GitHub + Linear first
  • Personal preference -> memory file (user/feedback type)
  • Reference info -> memory file (reference type) + MCP memory
  • Large document -> external data store + summary in memory
  • Conversation/session -> knowledge base repo + short summary in memory
2. Deduplicate

Check if this knowledge already exists:

  • Search memory files for existing entries
  • Query MCP memory with relevant terms
  • Check whether the information already exists in GitHub or Linear before creating another local note
  • Do not create duplicates. Update existing entries instead.
Show full SKILL.md (312 more words)Show less
3. Store

Write to appropriate layer(s):

  • Always update Claude Code memory for quick access
  • Use MCP memory for semantic searchability and relationship mapping
  • Update GitHub / Linear first when the information changes live project truth
  • Commit to the knowledge base repo for durable long-form additions
4. Index

Update any relevant indexes or summary files.

Sync Operations

Conversation Sync

Periodically sync conversation history into the knowledge base:

  • Sources: Claude session files, Codex sessions, other agent sessions
  • Destination: knowledge base repo
  • Generate a session index for quick browsing
  • Commit and push
Workspace State Sync

Mirror important workspace configuration and scripts to the knowledge base:

  • Generate directory maps
  • Redact sensitive config before committing
  • Track changes over time
  • Do not treat the knowledge base or archive folder as the live code workspace
GitHub / Linear Sync

When the information affects active execution:

  • update the relevant GitHub issue, PR, discussion, release notes, or roadmap thread
  • attach supporting docs to Linear when the work needs durable planning context
  • only mirror a local note afterwards if it still adds value
Cross-Source Knowledge Sync

Pull knowledge from multiple sources into one place:

  • Claude/ChatGPT/Grok conversation exports
  • Browser bookmarks
  • GitHub activity events
  • Write status summary, commit and push

Memory Patterns

# Short-term: current session context
Use TodoWrite for in-session task tracking

# Medium-term: project memory files
Write to ~/.claude/projects/*/memory/ for cross-session recall

# Long-term: GitHub / Linear / KB
Put active execution truth in GitHub + Linear
Put durable synthesized context in the knowledge base repo

# Semantic layer: MCP knowledge graph
Use mcp__memory__create_entities for permanent structured data
Use mcp__memory__create_relations for relationship mapping
Use mcp__memory__add_observations for new facts about known entities
Use mcp__memory__search_nodes to find existing knowledge

Best Practices

  • Keep memory files concise. Archive old data rather than letting files grow unbounded.
  • Use frontmatter (YAML) for metadata on all knowledge files.
  • Deduplicate before storing. Search first, then create or update.
  • Prefer one canonical home per fact set. Avoid parallel copies of the same plan across local notes, repo files, and tracker docs.
  • Redact sensitive information (API keys, passwords) before committing to Git.
  • Use consistent naming conventions for knowledge files (lowercase-kebab-case).
  • Tag entries with topics/categories for easier retrieval.

Quality Gate

Before completing any knowledge operation:

  • no duplicate entries created
  • sensitive data redacted from any Git-tracked files
  • indexes and summaries updated
  • appropriate storage layer chosen for the data type
  • cross-references added where relevant

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/knowledge-ops of affaan-m/ECC.

Open the folder on GitHubat commit ef648e0

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Knowledge Ops next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Knowledge Ops compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Knowledge Ops this skillaffaan-m/ECC276k2 repos~1.7kAutomated safety check: PassMIT
Copilot Spacesgithub/awesome-copilot40k1 repos~2.2kAutomated safety check: PassMIT
Basic Memory Setupbasicmachines-co/basic-memory4.1k—~3.9kAutomated safety check: PassAGPL-3.0
Frontmcp Guidesagentfront/frontmcp146—~6.3kAutomated safety check: PassApache-2.0
Liveagent Code ReviewStack-Cairn/LiveAgent2.2k—~2kAutomated safety check: PassMIT
Git Releasewesammustafa/opencode-primer398—~409Automated safety check: PassMIT

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Questions about Knowledge Ops

What does Knowledge Ops do?

Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Knowledge Ops is an agent skill from affaan-m/ECC. Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos).

When should I use Knowledge Ops?

Knowledge Ops fits situations like: the user wants to save; search across their knowledge systems.

How do I install Knowledge Ops in Claude Code?

Run `npx skills add affaan-m/ECC --skill knowledge-ops -a claude-code`. Or copy the skill folder (skills/knowledge-ops in affaan-m/ECC) into .claude/skills/knowledge-ops in your project. Claude Code loads it when a task matches its description.

How do I install Knowledge Ops in Codex?

Run `npx skills add affaan-m/ECC --skill knowledge-ops -a codex`. Or copy the skill folder (skills/knowledge-ops in affaan-m/ECC) into .agents/skills/knowledge-ops in your project. Codex loads it when a task matches its description.

Can I use Knowledge Ops in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill knowledge-ops -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/knowledge-ops, .gemini/skills/knowledge-ops, .github/skills/knowledge-ops and .opencode/skills/knowledge-ops in your project.

What does Knowledge Ops need to run?

SKILL.md names no scripts, command-line tools or credentials: Knowledge Ops is instructions for the agent only.

Does Knowledge Ops access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Knowledge Ops safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Knowledge Ops use?

Knowledge Ops is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Knowledge Ops use?

About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Knowledge Ops?

Skills that share tags, products or a category with Knowledge Ops: Copilot Spaces (github/awesome-copilot, 40k stars), Basic Memory Setup (basicmachines-co/basic-memory, 4.1k stars), Frontmcp Guides (agentfront/frontmcp, 146 stars) and Liveagent Code Review (Stack-Cairn/LiveAgent, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Knowledge Ops?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 275,546 GitHub stars. The repository holds 673 skills in this directory. The repository was last updated on October 5, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.