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 Zfinix/aster --skill long-running-workgit clone --depth 1 https://github.com/Zfinix/asterWrote 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/zfinix/aster/long-running-work)<a href="https://agentmods.dev/skills/zfinix/aster/long-running-work"><img src="https://agentmods.dev/badge/skills/zfinix/aster/long-running-work/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/zfinix/aster/long-running-work"><img src="https://agentmods.dev/badge/skills/zfinix/aster/long-running-work.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 | $0.00071 | $0.00618 |
| Opus 5.5 | $0.00028 | $0.00247 |
| Sonnet 5.5 | $0.00014 | $0.00124 |
| Haiku 4.5 | $0.00007 | $0.00062 |
Grade A, and why
long-running-work 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 4d 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
Long-running work
- Background anything long. Evals, benchmarks, full builds and test
suites, data jobs, servers, watchers:
run_commandwithbackground:true. It returns a job id at once and the job runs up to 4 hours. A foreground command is killed at its timeout, and a timeout is not a reason to narrow the work when the work is long by nature. - Load the skills before you start, not after it breaks. Read the skills
that cover the task (
build-triage,verify-before-done, the repo's own) first, and lay the steps out withupdate_planwhen there is more than one. Mark each step as it lands. - Make the run leave evidence. Write results to a file the run owns
(
results/run3.json,eval.log), not only to stdout: a job keeps just the tail of its output. Name each round so later rounds do not overwrite it. - Work while it runs. Start the job, then do the independent work: edit the next fix, update docs, review the diff, send read-only questions to background sub-agents. Do not edit files the running job reads.
- Wait, do not poll. When nothing is left to do,
command_jobaction:wait(up to 600 seconds per call) until it exits. Never calloutputin a loop, and neversleepin a shell to pass time. - Tell the user where things stand before every long wait. One or two plain sentences: what is running, what changed since the last round, what comes next. Example: "Round 3 is running. Since round 2 the system prompt is down from 91K to 44K characters, and all 727 tests pass."
- When it exits, read before you act. The exit message carries the code
and last output; read the result file for the real numbers. A non-zero exit
goes through
build-triage. Compare against the previous round and say what moved. - Close the loop. Fix what the round showed, run the next round the same
way, and stop when the goal is met or a round shows no progress. Stop jobs
you no longer need with action:
stop; never leave one running unexplained at the end of the work.
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.
- 4d ago First seen · 38 lines · 0 tokens per session scan A 5dc8d4faec8b
long-running-work is a skill published in the GitHub repository Zfinix/aster (132 stars, last pushed 4d ago), licensed Apache-2.0. It adds 71 tokens to every session and 618 once invoked, about $0.0003 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 2026-10-19.
Other skills, from other repositories
Evals
Assertion-first AI eval framework aligned to Anthropic's 'Demystifying evals for AI agents' — typed deterministic asserts + a forced-structured LLM judge over an input→assert case schema, pass^k/pass@k, capability vs regression suites, subscription-billed. USE WHEN eval, evaluate, benchmark, regression test…
Hardening
Hardens LifeOS tests via property/mutation testing. USE WHEN harden, hardening, property test, property based testing, PBT, fast-check, mutation test, mutation testing, Stryker, CRAP score, CRAP analysis, DRY scan, jscpd, acceptance test mutation, strengthen tests, sharpen ISCs, find bugs example tests miss, universal…
base
Universal coding patterns, constraints, TDD workflow, atomic todos.
ad-creative-v2
Ad Creative workflow skill. Use this skill when the user needs Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization and the operator…
armada-verification
Mandatory pre-completion verification and evidence checklist before reporting done.
refactor
Restructure code without changing observable behavior: rename, extract, inline, move, deduplicate, or replace an internal implementation with an equivalent one. Prove parity through unchanged pre-existing tests. Not for new behavior, bug fixes, explanation-only questions, or committing finished work.