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 agentmods add skills/av/harbor/timeboxed-iteratingnpx skills add av/harbor --skill timeboxed-iteratinggit clone --depth 1 https://github.com/av/harborWhat 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 | $0.00032 | $0.02152 |
| Opus 5 | $0.00016 | $0.01076 |
| Sonnet 5 | $0.00006 | $0.00430 |
| Haiku 4.5 | $0.00003 | $0.00215 |
Grade A, and why
timeboxed-iterating 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 3d 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 — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Timeboxed Iterating
Run a task iteratively via subagents for a user-specified duration. The clock is the only authority on when to stop. You are not.
Your Role
You are the orchestrator. You do exactly two things:
- Manage the clock — check time before every dispatch, stop when the deadline passes
- Dispatch subagents — give them the goal, the progress file path, and get out of the way
You do NOT do any actual work. No code changes, no file edits, no exploration, no analysis, no "quick fixes." All productive work happens inside subagents. Your context is reserved exclusively for the dispatch loop. If you catch yourself doing anything other than checking time, reading the progress file, and dispatching — stop. That work belongs in a subagent.
The Iron Law
YOU DO NOT DECIDE WHEN THE WORK IS DONE. THE CLOCK DECIDES.
Your only job is to keep dispatching useful work until the deadline passes. You have zero authority to judge completeness, sufficiency, or "good enough." The user gave you a duration. You use all of it.
Inputs
The user provides two things:
- Goal — what to do (e.g., "improve test coverage", "refactor AI slop", "build out the spec")
- Duration — how long to do it (e.g., "4 hours", "overnight", "90 minutes")
If the duration is vague ("overnight"), interpret it as 8 hours. If truly ambiguous, ask once.
The Process
digraph timeboxed {
rankdir=TB;
node [shape=box];
start [label="Record start time\nCompute deadline" shape=doublecircle];
init [label="Create progress file\nin /tmp"];
check [label="Check current time\nagainst deadline" shape=diamond];
read_log [label="Read progress file\nfor orchestrator context"];
dispatch [label="Dispatch subagent\nwith goal + progress file path"];
update [label="Update progress file\nwith iteration results"];
summary [label="Write final summary\nto progress file" shape=doublecircle];
start -> init -> check;
check -> read_log [label="time remains"];
check -> summary [label="deadline passed"];
read_log -> dispatch;
dispatch -> update;
update -> check;
}
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 193 lines · 32 tokens per session scan A d32cedd064ec
timeboxed-iterating is a skill published in the GitHub repository av/harbor (3,202 stars, last pushed 4d ago), licensed Apache-2.0. It adds 32 tokens to every session and 2,152 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.
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