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/prosusai/prism/audit-codenpx skills add ProsusAI/prism --skill audit-codegit clone --depth 1 https://github.com/ProsusAI/prismWhat 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 | $0.00027 | $0.02592 |
| Opus 5 | $0.00014 | $0.01296 |
| Sonnet 5 | $0.00005 | $0.00518 |
| Haiku 4.5 | $0.00003 | $0.00259 |
Grade A, and why
audit-code scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
import json, os, urllib.request, urllib.error How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use this skill
Use when the user wants to improve their codebase architecture by checking it against skills present in the registry. Invoked as /audit-code (Claude Code) or @audit-code (Cursor).
Configuration
- Primary source: All configured registries in
~/.prism/registries.json(with per-registry caching and source tagging) - Fallback 1: Local
skill-registry.jsonin the current project directory - Fallback 2: Local
_analysis/extracted_skills_codebase/skill directories - Authentication:
REGISTRY_TOKENenvironment variable (global override) or per-registry token fromregistries.json
Skills from multiple registries are merged and each result is tagged with
[registry-name](e.g.,[team],[community]) to identify the source.
Instructions
Step 1 -- Resolve skill registry source
Read ~/.prism/skills/_shared/registry-fetch.md and follow its instructions. It resolves all configured registries with ETag caching and local fallbacks, returning a skills array where each entry is tagged with _registry.
Outcomes:
- Valid JSON array → use as the skills list, proceed to Step 2
REGISTRY_EMPTY→ registry reached but empty, proceed to Step 2NO_REGISTRIES→ no registry reachable, stop (the shared file handles the user message)
Step 2 -- Check for empty registry
If the skills array from the resolved source is empty, respond with: "No skills have been published to the registry yet." and stop.
Step 2.5 -- Check for existing analysis files
Check which analysis files exist:
for f in _analysis/full_report.md _analysis/design.md _analysis/directives.md _analysis/incidents.md; do
test -f "$f" && echo "FOUND: $f" || echo "MISSING: $f"
done
If at least one file is found, list them and ask the user:
"Found existing analysis files in
_analysis/: {list found files}Use these for matching, or run a fresh codebase scan?"
- Fresh scan chosen → skip to Step 3, Path B.
- Use existing files chosen → read all found files now (see table below), then continue to Step 3, Path A.
- No files found → skip to Step 3, Path B.
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 · 230 lines · 27 tokens per session scan A 3513e8b9be45
audit-code is a skill published in the GitHub repository ProsusAI/prism (20 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 27 tokens to every session and 2,592 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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