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/rayforcedb/raysense/auditnpx skills add RayforceDB/raysense --skill auditgit clone --depth 1 https://github.com/RayforceDB/raysenseWhat 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 | $0.00055 | $0.00610 |
| Opus 5 | $0.00028 | $0.00305 |
| Sonnet 5 | $0.00011 | $0.00122 |
| Haiku 4.5 | $0.00006 | $0.00061 |
Grade A, and why
audit 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit
This skill is for deliberate "look at the whole codebase" requests. It calls multiple raysense MCP tools and produces a multi-section report. Do not run it as part of routine edits — it is loud by design and will pollute the working context.
All tools take a path argument; pass the current repo root.
Steps
- Architecture — call
raysense_architecture. Reports root causes, cycles by SCC, layer levels, and unstable modules. Lead the report with the worst root cause. - DSM — call
raysense_dsmfor the module dependency matrix and level assignments. Useful for showing the user the shape of the project, not just the metrics. - Evolution — call
raysense_evolution. Surfaces bus factor, change-coupling pairs (files that change together), and temporal hotspots (commits × max complexity). - Test gaps — call
raysense_test_gaps. Files without nearby tests, ranked by risk. - Optional dashboard — call
raysense_visualizeif the user asked for something they can browse. Writes a self-contained HTML file the user can open.
Report structure
When summarising back to the user, lead with the one finding that matters most — usually the worst architectural root cause or the highest-risk untested file. Long lists overwhelm; a single prioritized headline plus a short table of next-three-things tends to land better.
When to skip
- The user asked a narrow question. Use
impactor a single targeted MCP call instead. - The repo is tiny (under ~50 files). The audit will produce mostly
noise -- just call
raysense_healthand read out the grade.
See also
The audit's typed tools surface what raysense already knows. When
the user asks an audit-shaped question that doesn't fit a typed
tool, the query skill exposes Rayfall directly via
raysense_baseline_query:
- Custom architectural breakdowns -- group calls by caller module, count cross-layer imports, find ownership-by-language splits.
.graph.pagerank/.graph.louvain/.graph.betweennessover call_edges or module_edges for centrality-based audits.raysense_baseline_import_csvto bring external audit data (coverage, lint counts, test runtime) into the same query substrate as the structural baseline.
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 · 61 lines · 55 tokens per session scan A 8eac111224eb
audit is a skill published in the GitHub repository RayforceDB/raysense (11 stars, last pushed 4mo ago), licensed MIT. It adds 55 tokens to every session and 610 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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