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 agents/dannykkh/skill-olympus/chronos-workergit clone --depth 1 https://github.com/Dannykkh/skill-olympusWrote 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/agents/dannykkh/skill-olympus/chronos-worker)<a href="https://agentmods.dev/agents/dannykkh/skill-olympus/chronos-worker"><img src="https://agentmods.dev/badge/agents/dannykkh/skill-olympus/chronos-worker.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.00232 |
| Opus 5 | $0.00023 | $0.00116 |
| Sonnet 5 | $0.00009 | $0.00046 |
| Haiku 4.5 | $0.00005 | $0.00023 |
Grade A, and why
chronos-worker 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
Chronos Worker Compatibility Prompt
This file is a source-only compatibility adapter. Do not depend on the
chronos-worker name for persistence or routing. Load the canonical
auto-continue-loop skill and follow its Phase 1 cycle contract.
When an isolated cycle is useful, use the runtime's native general worker and pass only:
- the assigned scope and highest-priority actionable issue;
- the objective verification command and completion contract;
- the current
docs/chronos/chronos-log.mdstate and parked items; - the requirement to perform one minimal FIND -> FIX -> VERIFY -> LOG cycle.
The main Chronos harness owns the queue, retries, parked-item decisions, completion signal, and further cycles. A delegated worker must not delete or edit any loop-state file and must return evidence from the verification it actually ran.
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 · 27 lines · 46 tokens per session scan A 11c51d34a133
chronos-worker is an agent published in the GitHub repository Dannykkh/skill-olympus (5 stars, last pushed 3d ago), licensed MIT. It adds 46 tokens to every session and 232 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 2026-08-31.
Other agents, from other repositories
document-steward
GOAL: One document per domain. Minimum tokens for maximum clarity.
strategy-fidelity-voc
Evaluates app fidelity and completion against docs/SYSTEMARCHITECTURE.md and domain references. Serves as voice of customer: defines user workflows and outcomes, then validates implementation against them. Use proactively before releases, after major changes, or when validating feature completeness.
cross-project-memory
Designs and executes efficient cross-project and long-term memory so agents build apps better. Use when adding or improving memory that spans projects, sessions, or runs; when defining what to remember, how to scope it, and how to retrieve it for agent context.
architect
Software architecture lead for hybrid systems using traditional architecture (Next.js + PostgreSQL) and AI-agent-supportive architecture (ruvector). Use proactively for system design, module boundaries, interfaces, migration plans, and architecture trade-offs.
investigator
investigates a bug to identify root cause and set success criteria for resolution; creates investigation report for fixer agent to guide implementation.
ai-advocate
Audits the project for poor AI agent behaviors and recommends concrete improvements to make coding workflows more agent-friendly, reliable, and fast. Use proactively when agents struggle, loop, miss context, or produce inconsistent changes.