Borrowing it
Nothing to install: this file belongs to teejayen/arc. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/teejayen/arc/main/.claude/skills/knowledge-extraction/SKILL.mdgit clone --depth 1 https://github.com/teejayen/arcWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/teejayen/arc/knowledge-extraction)<a href="https://agentmods.dev/skills/teejayen/arc/knowledge-extraction"><img src="https://agentmods.dev/badge/skills/teejayen/arc/knowledge-extraction/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/teejayen/arc/knowledge-extraction"><img src="https://agentmods.dev/badge/skills/teejayen/arc/knowledge-extraction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.00484 |
| Opus 5.5 | $0.00014 | $0.00194 |
| Sonnet 5.5 | $0.00007 | $0.00097 |
| Haiku 4.5 | $0.00004 | $0.00048 |
Grade A, and why
knowledge-extraction scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Knowledge Extraction
Capture learnings, patterns, and reusable knowledge from conversations.
When to Use
- A useful pattern or approach emerged
- Something was learned that's worth remembering
- A solution was found that might apply elsewhere
- User explicitly wants to save knowledge
Execution Steps
Step 1: Identify the knowledge
Types of extractable knowledge:
- How-to: Process or technique
- Pattern: Recurring approach or structure
- Insight: Understanding about how something works
- Reference: Facts or information worth keeping
- Lesson: Learning from experience (including failures)
Step 2: Determine destination
| Knowledge Type | Destination |
|---|---|
| Technical how-to | areas/learning/[topic].md |
| Life pattern | areas/[relevant-area]/patterns.md or standalone |
| Project insight | areas/[project]/learnings.md |
| General reference | resources/[topic]/ |
| Tool/product knowledge | resources/tools/[tool].md |
Step 3: Create knowledge file
---
title: "[Clear descriptive title]"
created: YYYY-MM-DD
tags: [knowledge, topic, source-area]
type: [how-to|pattern|insight|reference|lesson]
---
# [Title]
## Summary
[One paragraph - what this knowledge is and why it matters]
## The Knowledge
### Context
[When/where this applies]
### Detail
[The actual knowledge - steps, pattern description, insight explanation]
### Examples
[If applicable - concrete examples of application]
## Caveats
[If applicable - when this doesn't apply, edge cases]
## Source
[Where this came from - session reference, experience, external source]
## Related
- [[related-notes]]
Step 4: Link appropriately
- Add reference in relevant area/project files
- Update any index files if they exist
- Note in session file that knowledge was extracted
Step 5: Confirm
- Show file location
- Summarise what was captured
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 84 lines · 36 tokens per session scan A 8f51a5d0aaff
knowledge-extraction is a skill published in the GitHub repository teejayen/arc (5 stars, last pushed 9mo ago), licensed MIT. It adds 36 tokens to every session and 484 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
knowledge-extraction compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| knowledge-extractionteejayen/arc | Skill | 5 | 9mo ago | MIT | A | 36 | Claude Code |
| knowledge-ingestopenclaw/openclaw | Skill | 394k | yesterday | MIT | A | 80 | Claude Code, Codex |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 68k | 2d ago | Apache-2.0 | A | 217 | Claude Code, Codex |
| forgetasgeirtj/system_prompts_leaks | Skill | 71k | 2d ago | CC0-1.0 | A | 74 | Claude Code, Codex |
| Cortexdanielmiessler/LifeOS | Skill | 20k | yesterday | MIT | A | 184 | Claude Code |
| memoryopensquilla/opensquilla | Skill | 7.1k | 6d ago | Apache-2.0 | A | 44 | Claude Code, Codex |
| ha-data-storesshiwenwen/hope-agent | Skill | 1.9k | yesterday | MIT | A | 115 | Claude Code, Codex |