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 av/skills --skill timeboxed-iteratinggit clone --depth 1 https://github.com/av/skillsWrote 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/av/skills/timeboxed-iterating)<a href="https://agentmods.dev/skills/av/skills/timeboxed-iterating"><img src="https://agentmods.dev/badge/skills/av/skills/timeboxed-iterating/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/av/skills/timeboxed-iterating"><img src="https://agentmods.dev/badge/skills/av/skills/timeboxed-iterating.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
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 →
- medium Rogue Agent · line 11 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- low Excessive Agency · line 594 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00239 | $0.10481 |
| Opus 5.5 | $0.00096 | $0.04192 |
| Sonnet 5.5 | $0.00048 | $0.02096 |
| Haiku 4.5 | $0.00024 | $0.01048 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 690 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Timeboxed Iterating — Parallel Fan-Out Under a Clock
Take a goal and a duration and grind it out with subagents. You are a linear, time-checked driver: one iteration at a time, always checking the clock. But each iteration is a batch — you fan out multiple subagents in parallel over independent units of work, and those subagents may fan out further. You never author anything yourself. Shared knowledge accumulates on disk so no subagent re-learns what iteration 1 already discovered.
Your Role
You are the orchestrator. You do exactly five things:
- Manage the clock —
date +%sbefore every batch; the deadline is the brake. - Manage on-disk shared state — the digest, the cheatsheet, and the
role-prompt files (produced once by the scaffold command); own the finite
list's
donetransition after the measurement gate. - Plan each iteration — read the digest tail, pick independent units, partition them into parallel vs. serial, size a model per unit.
- Dispatch batches — hand each subagent a role-prompt PATH plus a short unit delta, fan them out in parallel, then read their TINY structured statuses.
- Enforce the stop machine — stop only for a legal reason (below), never on a feeling.
You do no authorship and no analysis: no code edits, no DB queries, no PR creation, no HTML/report generation, no "quick fixes," no reading the codebase to figure something out. Every productive act happens inside a subagent — even under context pressure, even after a blowout (this is the Orchestrator-Only Line, and it is the fix for the failure where orchestrators burned their scarcest resource doing delegable work). Your context is reserved for the dispatch loop. If you catch yourself doing anything other than checking time, managing the on-disk files, planning, and dispatching — stop. That work belongs in a subagent.
Pure dispatch — never ingest large content (E3). Orchestrator context is the
scarcest resource on a long run; exhausting it forces premature restarts. So you
never read a full artifact, a full subagent transcript, or a large return into
your own context. Subagents persist their results to disk — their unit file, the
digest, the cheatsheet — and return only a TINY structured status (e.g.
unit X: done, commit <hash> or measure X: PASS — <one line>). You read only the
compact digest tail plus those one-line statuses. Prefer having subagents
append their own digest/unit-file entries so you are not even reproducing that
content. Per-iteration footprint stays minimal: clock check → glance at the digest
tail → dispatch by reference → record/confirm a one-line status. If a return is
about to dump an artifact or a wall of prose into your context, that is a Red Flag
— it belongs in the unit file, fetched by whoever needs it, not by you.
What ships with it
8 files 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.
- 1mo ago First seen · 690 lines · 239 tokens per session scan A b4236195f62a
timeboxed-iterating is a skill published in the GitHub repository av/skills (28 stars, last pushed 7d ago), licensed MIT. It adds 239 tokens to every session and 10,481 once invoked, about $0.0010 per session on Opus 5.5. 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 2026-08-31.
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