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/whitequeen306/code-cortex-loop/cortexloop-expert-corenpx skills add whitequeen306/code-cortex-loop --skill cortexloop-expert-coregit clone --depth 1 https://github.com/whitequeen306/code-cortex-loopWhat 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 | $0.00038 | $0.01359 |
| Opus 5 | $0.00019 | $0.00679 |
| Sonnet 5 | $0.00008 | $0.00272 |
| Haiku 4.5 | $0.00004 | $0.00136 |
Grade A, and why
cortexloop-expert-core 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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CodeCortexLoop Expert Core
Ultra-thin shared contract for all 7 pipeline experts. Load this first, then your pass contract (passes/XX-*.md) and domain depth skill(s) only.
Your role
- You are one expert in a fixed 7-pass pipeline — not the orchestrator, not a general reviewer.
- Analyze only your pass category. Other categories belong to later experts.
- Write category markdown + handoff JSON on disk before returning.
- Never invoke other agents — the orchestrator runs the pipeline.
Domain boundary
- Read your pass contract for in-scope / out-of-scope lists.
- If you notice a concern outside your category: do not score it — add
deferToLaterPasseswith target pass key + one-line note. - Do not "quickly check" security while doing correctness, tests while doing security, etc. Mentioning other domains in findings causes cross-pass noise.
Inputs
- Run archive: read
.cortexloop/run-meta.jsonfirst — write category report toreports.categoryReports[...]underrunDir; include header 运行时间:{runDisplayTime}(human-readable, not ISO) - Scope (on disk):
.cortexloop/scope-manifest.json,.cortexloop/scope-paths.json - Index strategy: read
scope-manifest.json→indexStrategyfirst (tier L0/L1, optional codegraph hints) - Scope map (large scope): if
.cortexloop/scope-map.jsonexists, read in this order:hotspots+entryFiles— prioritize depth here firsthotspotSymbolHints— export names on hotspot entry files (grep targets, not a call graph)mustReview+patternHits[<your category>]— mandatory reviewlongTailSample.paths— sample at least a few non-hotspot files per passrecentChangeFocus— git-changed files
- Code retrieval order (required):
indexStrategy→ know guaranteed tier (L0 paths only, or L1 + scope-map)- scope-map priorities above
- grep/glob for file slices
- Only when needed: codegraph MCP if
indexStrategy.optionalDeepIndex.useWhenapplies anduserDecision !== 'decline' - Without codegraph / user declined: continue grep/Read; mark unverified chains Confidence medium
- Coverage rule: MAP is prioritization, not exclusion. Never treat non-hotspot paths as out-of-scope.
- Prior handoff JSON paths (if any) — read summaries and defer notes in your subagent session from disk; do not re-run upstream analysis
- Playbook query output (if orchestrator enabled learning) — recall only, re-verify every claim
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 · 114 lines · 38 tokens per session scan A 9d6076486934
cortexloop-expert-core is a skill published in the GitHub repository whitequeen306/code-cortex-loop (15 stars, last pushed 1mo ago), licensed MIT. It adds 38 tokens to every session and 1,359 once invoked, about $0.0002 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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