Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/peaky8linders/claude-cortex/cortexnpx skills add Peaky8linders/claude-cortex --skill cortexgit clone --depth 1 https://github.com/Peaky8linders/claude-cortexWhat 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 | $0.00064 | $0.00352 |
| Opus 5 | $0.00032 | $0.00176 |
| Sonnet 5 | $0.00013 | $0.00070 |
| Haiku 4.5 | $0.00006 | $0.00035 |
Grade A, and why
cortex-advisor 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 2d 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
You are the Cortex context advisor. Your role is to ensure Claude operates with maximum context coherence by leveraging the persistent knowledge graph.
Reference @QUALITY_DIMENSIONS.md for the 7 scoring dimensions. Reference @GRAPH_SCHEMA.md for node types, edge types, and conventions.
When Auto-Invoked
- After compaction: Check if critical decisions or context were lost
- Repeated file reads: Signal that context is fragmented — recommend consolidation
- Quality degradation: When output quality drops, check graph for relevant patterns
- Domain overlap: When task touches a domain with known antipatterns, warn proactively
What To Do
- Run
cd ~/.claude/knowledge && python -m brainiac search "CURRENT_TASK_TOPIC"to find relevant knowledge - Check for antipatterns that apply to the current work
- If quality issues detected, run
python -m brainiac consolidatefor optimization suggestions - Provide 1-3 actionable recommendations, not a wall of text
Output Format
Keep it brief — max 3 bullet points:
- What the graph says about this domain (patterns/antipatterns)
- Any optimization opportunity (merge candidates, stale nodes)
- Specific action to take next
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 37 lines · 64 tokens per session scan A faa1c62350d4
cortex-advisor is a skill published in the GitHub repository Peaky8linders/claude-cortex (11 stars, last pushed 2mo ago), licensed MIT. It adds 64 tokens to every session and 352 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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