Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/giggsoinc/ravennpx agentmods add skills/giggsoinc/raven/raven-dashboardWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/giggsoinc/raven/raven-dashboard)<a href="https://agentmods.dev/skills/giggsoinc/raven/raven-dashboard"><img src="https://agentmods.dev/badge/skills/giggsoinc/raven/raven-dashboard/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/giggsoinc/raven/raven-dashboard"><img src="https://agentmods.dev/badge/skills/giggsoinc/raven/raven-dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00098 | $0.00846 |
| Opus 5.5 | $0.00039 | $0.00338 |
| Sonnet 5.5 | $0.00020 | $0.00169 |
| Haiku 4.5 | $0.00010 | $0.00085 |
Grade A, and why
raven-dashboard 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 1mo 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/raven-dashboard
Generates the Tokenomics & Usage Dashboard with a full metadata block and a rule-based recommendations engine.
How to invoke
On demand (user said "raven dashboard"): open default browser, this repo:
python3 scripts/memory/ide-boot.py
# CLI (terminal-friendly ASCII)
python3 .claude/scripts/dashboard.py --cli
# Obsidian markdown (writes ~/RavenVault/Dashboard.md)
python3 .claude/scripts/dashboard.py --obsidian
# Static HTML report with download buttons
python3 .claude/scripts/dashboard.py --html --open
# All three at once
python3 .claude/scripts/dashboard.py --all
# Raw metrics JSON (for piping)
python3 .claude/scripts/dashboard.py --json
Filters
--days N— reporting window in days (default 30)--month YYYY-MM— specific month--project NAME— filter to one project (default: all)
What it includes
- Metadata block — report timestamp (UTC + local), plugin version, project, company, owner, user, git branch, git remote, manifest presence, vault path
- Manifest snapshot — project, owner, version, stack, standards, approval mode
- Last session — tokens, cost, tier breakdown
- Cumulative window — sessions, total tokens, total cost, avg/session
- Tier mix — SIMPLE/MEDIUM/COMPLEX/LOCAL_ONLY share, cost, distribution bar
- Daily series — sessions/tokens/cost per day
- Top skills + specialists — invocation counts
- Guard events — violation + approval breakdown
- Recommendations — rule-based, severity-coded (🔴 high · 🟡 medium · 🔵 info), with estimated savings where applicable
Recommendations engine — rules
| Rule | Trigger | Severity | Suggested action |
|---|---|---|---|
| Opus over-classification | COMPLEX share > 30% | 🔴 high | Review prompts, tune model.env |
| Opus zero rate | 0% COMPLEX over 5+ sessions | 🔵 info | Verify router wiring |
| High avg cost/session | > $1.00 | 🟡 medium | Use /clear, lower autocompact pct |
| High avg tokens/session | > 50,000 | 🟡 medium | Compress CLAUDE.md, trim skills |
| Guard violations trending | > 10 in window | 🔴 high | Address top violation root cause |
| Frequent approval overrides | > 5 | 🟡 medium | Codify exceptions in manifest |
| No vault sessions | sessions/ dir empty | 🔴 high | Check obsidian-log Stop hook |
| Specialist concentration | One spec > 70% | 🔵 info | Check router wiring |
| Missing manifest | .raven/manifest.json absent |
🔴 high | Run /raven-init (Andie auto-onboards) |
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.
- 1mo ago First seen · 91 lines · 98 tokens per session scan A 34df8668e591
raven-dashboard is a skill published in the GitHub repository giggsoinc/raven (5 stars, last pushed 13d ago), licensed MIT. It adds 98 tokens to every session and 846 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-03.
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