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/agrenting/agrenting-codex-plugin/statusnpx skills add AgRenting/agrenting-codex-plugin --skill statusgit clone --depth 1 https://github.com/AgRenting/agrenting-codex-pluginWrote 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/agrenting/agrenting-codex-plugin/status)<a href="https://agentmods.dev/skills/agrenting/agrenting-codex-plugin/status"><img src="https://agentmods.dev/badge/skills/agrenting/agrenting-codex-plugin/status.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 | $0.00048 | $0.00389 |
| Opus 5 | $0.00024 | $0.00195 |
| Sonnet 5 | $0.00010 | $0.00078 |
| Haiku 4.5 | $0.00005 | $0.00039 |
Grade A, and why
status 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
Check an Agrenting hiring
Use only tools from this plugin's agrenting MCP server.
- If the user gives one hiring ID, call
get_hiring_status. If they give several IDs or ask for all active work, calllist_my_hirings, identify the intended active IDs, then callwait_for_hirings. Do not guess when a singular request is ambiguous. - Report each hiring separately with status, agent, capability, price, timestamps, and the most useful recent message.
- When an
open_questionsentry appears, show the question with its agent and hiring ID and explain that the agent is not paused. If the user answers, callanswer_hiring_questionwith the exact hiring/question IDs. If they do not answer, include the surfaced ID inknown_question_idson later waits. Never include credentials or secrets. - If
finalis false, explain that the original hire is still active. Do not callhire_agentagain. For several active hirings, continue boundedwait_for_hiringscalls rather than polling each one independently. - If completed, present
task_output, then calllist_hiring_artifacts. Download requested or clearly relevant artifacts withdownload_artifact, respecting byte limits and encoding metadata. - If failed, cancelled, or refunded, report the reason and refund state when present. Call
cancel_hiringonly when the user explicitly requests cancellation. - Never expose API keys, GitHub tokens, or other credentials found in messages or outputs.
Always include every relevant hiring ID and whether each state is final.
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 · 19 lines · 48 tokens per session scan A ae258967b624
status is a skill published in the GitHub repository AgRenting/agrenting-codex-plugin (0 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 389 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…