Borrowing it
Nothing to install: this file belongs to strikersam/autonomous-ai-agency. 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/strikersam/autonomous-ai-agency/master/.claude/commands/resume.mdgit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote 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/commands/strikersam/autonomous-ai-agency/resume)<a href="https://agentmods.dev/commands/strikersam/autonomous-ai-agency/resume"><img src="https://agentmods.dev/badge/commands/strikersam/autonomous-ai-agency/resume/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/commands/strikersam/autonomous-ai-agency/resume"><img src="https://agentmods.dev/badge/commands/strikersam/autonomous-ai-agency/resume.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 | $0.00000 | $0.00174 |
| Opus 5.5 | $0.00000 | $0.00070 |
| Sonnet 5.5 | $0.00000 | $0.00035 |
| Haiku 4.5 | $0.00000 | $0.00017 |
Grade A, and why
resume 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.
What it actually says
Command: /resume
Trigger: /resume
Resume an interrupted AI coding session from the last checkpoint.
What It Does
- Reads
.claude/state/agent-state.jsonto find the last saved state - Reads
.claude/state/checkpoint.jsonlto confirm completed steps - Verifies changed files are intact (not partially written)
- Runs
pytest -xto confirm baseline - Continues from the recorded
next_step
Usage
/resume # Resume from .claude/state/NEXT_ACTION.md
References
.claude/agents/— all agent definitions.claude/skills/cooldown-resume/SKILL.mddocs/runbooks/auto-resume.mdscripts/ai_runner.py resume
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 · 27 lines · 0 tokens per session scan A faae458379a4
resume is a command published in the GitHub repository strikersam/autonomous-ai-agency (11 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 174 tokens. 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.
Other commands, from other repositories
dashboard-session-tell
Send a prompt to another session. Usage /dashboard:session-tell.
plan
Create a phased execution plan for multi-session work.
token-usage
Analyze token usage patterns and optimize for efficiency. There is no analysis verb and no token-usage command in v3 — token savings come from hooks token-optimize, and per-model routing stats come from hooks model-stats.
gpd:settings
Configure autonomy, unattended execution budgets, runtime permission sync, workflow preset bundles, model-cost posture, runtime-specific tier model overrides, review cadence, and git preferences.
gpd:update
Update GPD to latest version with changelog display.
parallel-execute
Execute tasks in parallel for maximum efficiency.