Borrowing it
Nothing to install: this file belongs to egregore-labs/egregore. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/egregore-labs/egregore/main/.claude/skills/dashboard/SKILL.mdgit clone --depth 1 https://github.com/egregore-labs/egregoreWrote 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/egregore-labs/egregore/dashboard)<a href="https://agentmods.dev/skills/egregore-labs/egregore/dashboard"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/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/egregore-labs/egregore/dashboard"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 160 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00036 | $0.03157 |
| Opus 5 | $0.00018 | $0.01579 |
| Sonnet 5 | $0.00007 | $0.00631 |
| Haiku 4.5 | $0.00004 | $0.00316 |
Grade A, and why
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 9d 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 — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
See your recent sessions, open handoffs, and current work at a glance.
Display it immediately — no preamble, no narration, no reasoning text. The rendered box must be the FINAL text of the turn — never follow it with AskUserQuestion in the same turn. The harness hides text that precedes a tool call, so a box rendered before AskUserQuestion is never seen by the user.
When to invoke
User says: "what did I work on", "my dashboard", "show me my work", "what's my status", "what have I done", "my sessions", "my progress", "what's open", "where was I"
Not this: team-wide view → /activity · ending session → /wrap · pushing work → /save
Topic: $ARGUMENTS
Execution rules
CRITICAL: Suppress raw output. Never show raw JSON. Shell variables do NOT persist between tool calls, so DATA=$(...) alone cannot hide it — use the temp-file + compact-slice pattern in Step 1.
One data call. bash bin/dashboard-data.sh returns everything as JSON. Do NOT call bin/graph.sh directly.
Render immediately. No "Let me check..." or "Here's your dashboard...". Straight to the TUI box.
Step 1: Fetch data
Map $ARGUMENTS to time range:
- (empty) →
P7D today→P1Dweek→P7Dmonth→P30Dall→P365D
Quiet fetch — never print the raw JSON. This command renders inline (terminal-render, undelegatable), so a bare data-script call dumps hundreds of JSON lines into the terminal before the box. Write to a temp file and read compact slices, in ONE command:
DATA="${TMPDIR:-/tmp}/egregore-dashboard-$$.json"
bash bin/dashboard-data.sh "" "$TIME_RANGE" > "$DATA" 2>/dev/null
jq -c '{me, org, date, range_label, graph_status, graph_reason, stats, current_session, identity_hint, git}' "$DATA"
jq -c '.sessions[:8][] | {id, date, topic, branch, status, handedTo}' "$DATA"
jq -c '(.todos[:8][] | {id, text: (.text | tostring | .[0:120]), status, priority, quest}), (.quests[:5][]), (.handoffs[:5][]), (.open_threads[:5][])' "$DATA"
rm -f "$DATA"
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.
- 9d ago First seen · 274 lines · 36 tokens per session scan A 46225f03d4bf
dashboard is a skill published in the GitHub repository egregore-labs/egregore (282 stars, last pushed 5d ago), licensed MIT. It adds 36 tokens to every session and 3,157 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.
Other skills, from other repositories
sw-handoff
Write a portable, secret-scrubbed handoff doc plus a diff of your uncommitted edits so another tool or machine resumes where you stopped. Use for "handoff", "out of tokens", "switch to Codex".
tokf-discover
Find missed token savings by scanning AI coding session files for commands that ran without tokf filtering.
handoff
Write a portable, secret-scrubbed handoff doc so this work can continue in any AI tool or on any machine. Use when saying "handoff", "running out of tokens", or "continue elsewhere".
feishu-openapi-skill
Operate Feishu or Lark IM APIs through UXC with a curated OpenAPI schema, tenant-token bearer auth, and chat/message guardrails.
slack-openapi-skill
Operate Slack Web API through UXC with a curated OpenAPI schema, bearer-token auth, and messaging-core guardrails.
claude-code-expert
Especialista profundo em Claude Code - CLI da Anthropic. Maximiza produtividade com atalhos, hooks, MCPs, configuracoes avancadas, workflows, CLAUDE.md, memoria, sub-agentes, permissoes e integracao com ecossistemas.