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/strikersam/autonomous-ai-agencynpx agentmods add skills/strikersam/autonomous-ai-agency/cooldown-resumeWrote 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/strikersam/autonomous-ai-agency/cooldown-resume)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/cooldown-resume"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/cooldown-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/skills/strikersam/autonomous-ai-agency/cooldown-resume"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/cooldown-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 | $0.00031 | $0.00827 |
| Opus 5 | $0.00015 | $0.00413 |
| Sonnet 5 | $0.00006 | $0.00165 |
| Haiku 4.5 | $0.00003 | $0.00083 |
Grade B, and why
cooldown-resume scanned grade B with 1 finding 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 12d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat .claude/state/NEXT_ACTION.md How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: cooldown-resume
When to Use
Use this skill immediately after:
- A coding session was interrupted by token exhaustion
- Rate limiting or quota exhaustion stopped a task
- A process restart wiped in-memory state
- You are starting a new session and need to continue previous work
Instructions
Step 1 — Read the checkpoint files
# Human-readable next action
cat .claude/state/NEXT_ACTION.md
# Machine-readable full state
cat .claude/state/agent-state.json
# Ordered log of completed steps
cat .claude/state/checkpoint.jsonl
Or use the AI runner:
python scripts/ai_runner.py status
Step 2 — Assess the state
From agent-state.json, determine:
completed_steps— what is already done (do NOT redo these)next_step— what to do nextchanged_files— what files were modified (check their current state)pending_risks— any known issues or blockers
Step 3 — Verify changed files are correct
For each file in changed_files, read the current content to confirm
the change was fully applied (not half-written due to interruption).
If a file appears partially written:
- Read the file fully.
- Compare with what the step description says it should contain.
- Complete or revert the partial change before continuing.
Step 4 — Run tests to confirm baseline
pytest -x
If tests fail after resuming:
- Read the test error carefully.
- Check if it is related to a partial change from the interrupted session.
- Fix the partial change, then re-run tests.
Step 5 — Continue from next_step
Execute only the steps that are NOT in completed_steps.
After each sub-step completes, append to .claude/state/checkpoint.jsonl:
{"ts":"<ISO8601>","step":"<step-id>","status":"done","detail":"<what was done>"}
And update .claude/state/agent-state.json:
- Move the step from plan to
completed_steps - Update
next_stepto the following step - Update
last_updated
Step 6 — Use the watchdog for future sessions
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.
- 12d ago First seen · 120 lines · 31 tokens per session scan B c90ad3232423
cooldown-resume is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It adds 31 tokens to every session and 827 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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