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/sylphxai/coderag/locusnpx skills add SylphxAI/coderag --skill locusgit clone --depth 1 https://github.com/SylphxAI/coderagWhat 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 | $0.00000 | $0.00060 |
| Opus 5 | $0.00000 | $0.00030 |
| Sonnet 5 | $0.00000 | $0.00012 |
| Haiku 4.5 | $0.00000 | $0.00006 |
Grade A, and why
locus 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 3d 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
Locus — local code search
npx @sylphx/locus --root=/absolute/path/to/project
Primary: codebase_search (and related search ops owned by this package).
Not architecture path/impact (use Spine). Not filesystem writes.
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.
- 3d ago First seen · 9 lines · 0 tokens per session scan A 6a8179a8aee3
locus is a skill published in the GitHub repository SylphxAI/coderag (12 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 60 tokens. 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.
Other skills, from other repositories
extract-entities
Extract people, organizations, dates, amounts, or custom labels from a document through the connected Superlinked MCP edge, returning a compact table instead of reading the full document into context. Use when the user asks to list, extract, or tabulate entities from a file.
parse-document
Convert a PDF, scan, image of a page, or office file to clean markdown through the connected Superlinked MCP edge, so the source document is not read into model context directly. Use when the user asks to read, parse, OCR, extract from, summarize, or answer questions about a document.
redact-pii
Redact personal data from a document through the connected Superlinked MCP edge before working with the content. Use when the user asks to redact, anonymize, scrub, de-identify, or remove PII/sensitive data from a document.
summarize-document
Summarize a long PDF, scan, office file, text file, or markdown file through the connected Superlinked MCP edge instead of reading the whole source into model context. Use when the user asks for a summary, overview, digest, or "what does this document say" about a large file.
superlinked-docs
Offload document, image, and structured-output work to the Superlinked inference cluster: convert PDF/DOCX/PPTX/XLSX/HTML/scans to clean markdown, describe an image (caption + tags), or produce schema/grammar-constrained JSON off the cluster — instead of ingesting the file directly, which can reduce the tokens billed…
codebase-search
Semantic code and documentation search by meaning. Use codebasepeek to find WHERE code is (saves tokens), codebasesearch to see actual code. For exact identifiers, use grep instead. Search local codebase before using websearch for code/library/API/example questions.