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 skills add cenconq25/claude-code-app-studio --skill team-live-opsgit clone --depth 1 https://github.com/cenconq25/claude-code-app-studioWrote 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/cenconq25/claude-code-app-studio/team-live-ops)<a href="https://agentmods.dev/skills/cenconq25/claude-code-app-studio/team-live-ops"><img src="https://agentmods.dev/badge/skills/cenconq25/claude-code-app-studio/team-live-ops/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/cenconq25/claude-code-app-studio/team-live-ops"><img src="https://agentmods.dev/badge/skills/cenconq25/claude-code-app-studio/team-live-ops.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 | $0.00054 | $0.01945 |
| Opus 5 | $0.00027 | $0.00972 |
| Sonnet 5 | $0.00011 | $0.00389 |
| Haiku 4.5 | $0.00005 | $0.00194 |
Grade A, and why
team-live-ops 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 6d 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 — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team Live Ops
Post-launch planning is its own discipline. This skill coordinates the five roles that turn telemetry, user feedback, and roadmap into a shippable live-ops cycle (a season, an event, or a live content update).
Team Composition
- live-ops-designer — the cycle plan, content beats, pacing.
- monetization-designer — pricing experiments, paywall variants, promotion calendar.
- analytics-engineer — telemetry health, KPI targets, dashboards, experiment instrumentation.
- community-manager — communications, feedback loop, community events.
- content-strategist — copy direction, narrative continuity, cross-channel messaging.
Spawn each via Task. Run independent subagents in parallel where their inputs are independent.
Phase 1: Context Load
Read in parallel:
production/stage.txt— confirm we are inlive-opsorrelease.- Latest milestone in
production/milestones/. - Latest release log in
production/releases/. - Latest
/balance-checkand/perf-profileartifacts. production/qa/bugs/for top user-facing pain points.- Any analytics summary in
production/analytics/. - Any prior live-ops cycle plans in
production/live-ops/.
Confirm with the user the cycle type and duration:
- season — typically 6-12 weeks of themed content.
- event — 3-14 days, narrowly scoped.
- update — feature drop or balance pass, no theme.
Phase 2: Telemetry Snapshot via analytics-engineer
Spawn analytics-engineer via Task. Prompt template:
Pull the last [N weeks] of data. Summarize: DAU/MAU, retention curves (D1, D7, D30), conversion funnel rates, ARPDAU, paid-user share, churn drivers, top crash signatures. Highlight any deltas vs the previous window. Identify segments worth special attention.
Render the analytics summary. Ask the user which 1-3 metrics this cycle should move.
Phase 3: Content Plan via live-ops-designer
Spawn live-ops-designer via Task. Prompt template:
Cycle type: [type]. Duration: [N weeks]. KPI targets from analytics: [list]. Recent user feedback themes: [list]. Compose a content beat plan: weekly/daily beats, hero moments, evergreen content, lapsed- user re-engagement hooks. Identify what content production needs are upstream (assets, copy, code).
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.
- 6d ago First seen · 287 lines · 54 tokens per session scan A 6d2205fcb8d5
team-live-ops is a skill published in the GitHub repository cenconq25/claude-code-app-studio (40 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 1,945 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 2026-09-03.
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