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/activity/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/activity)<a href="https://agentmods.dev/skills/egregore-labs/egregore/activity"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/activity/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/activity"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/activity.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 109 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 | $0.00043 | $0.04219 |
| Opus 5 | $0.00022 | $0.02109 |
| Sonnet 5 | $0.00009 | $0.00844 |
| Haiku 4.5 | $0.00004 | $0.00422 |
Grade A, and why
activity 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 — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
See what's happening across the team — recent sessions, handoffs, and open work.
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: "catch me up", "what's going on", "show dashboard", "where did I leave off", "what happened", "any updates", "what did I miss" Not this: if user wants to do something specific, route to that command instead
Topic: $ARGUMENTS
Step 1: Fetch data
Quiet fetch — never print the raw JSON. The payload runs to several hundred lines; since this command renders inline (terminal-render, undelegatable), a bare bash bin/activity-data.sh dumps that JSON into the user's terminal before the board — burying the thing this command exists to show. Write it to a temp file and read only compact slices, in ONE command:
DATA="${TMPDIR:-/tmp}/egregore-activity-$$.json"
bash bin/activity-data.sh > "$DATA" 2>/dev/null
jq -c '{me, org, date, graph_status, graph_reason, todos_merged, knowledge_gap, orphans, trends}' "$DATA"
jq -c '.handoffs_to_me[] | {topic, date, author, status, sessionId, filePath, response}' "$DATA"
jq -c '(.pending_questions[] | {setId, topic, from, created}), (.answered_questions[] | {topic, answeredBy})' "$DATA"
jq -c '(.my_sessions[:6][] | {date, topic, id}), (.team_sessions[:6][] | {date, topic, by}), (.checkins[:5][] | {date, by, summary})' "$DATA"
jq -c '(.quests[:5][] | {quest, artifacts, daysSince}), (.prs[:6][] | {number, title, author}), {pr_count: (.prs | length)}' "$DATA"
jq -c '(.focus_history[:3][] | {selected, dismissed}), {disk: .disk}' "$DATA"
rm -f "$DATA"
One compact line per record — everything the render needs, nothing else. If a later step needs a field not sliced above (e.g. /activity quests wants all quests, or a handoff's all_handoffs row), re-fetch and run another targeted jq — never cat the file, never run the data script bare.
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 · 263 lines · 43 tokens per session scan A b5edf570f170
activity is a skill published in the GitHub repository egregore-labs/egregore (282 stars, last pushed 5d ago), licensed MIT. It adds 43 tokens to every session and 4,219 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
dream
Batch-execute SHIP-ready wishes overnight — pick wishes, orchestrate workers, review PRs, wake up to results.
clickup
Use when managing ClickUp tasks, sprints, or comments via the cup CLI tool. Triggers: task queries, status updates, sprint tracking, creating subtasks, posting comments, threaded replies, standup summaries, searching tasks, checking overdue items, assigning tasks, listing spaces and lists, opening tasks in browser…
sw-do
Implement a SpecWeave increment task by task through the ledger, with evidence per task and a verified close. Use for "implement this", "start working", "continue the increment", "keep going".
done
Close an increment: ledger check, specweave verify, optional review, then specweave complete. Use when all tasks are done and saying "close increment", "we are done", or "finish up".
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".
genie-orca-wish
Turn a brainstorm/design into an APPROVED-able wish whose Dispatch plan is the literal input to Orca tasks and Linear issues. High-reasoning pass: pre-decide everything so fast workers can execute without judgment calls.