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/mlops-courses/agentops-open-course/remediationnpx skills add MLOps-Courses/agentops-open-course --skill remediationgit clone --depth 1 https://github.com/MLOps-Courses/agentops-open-courseWrote 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/mlops-courses/agentops-open-course/remediation)<a href="https://agentmods.dev/skills/mlops-courses/agentops-open-course/remediation"><img src="https://agentmods.dev/badge/skills/mlops-courses/agentops-open-course/remediation.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 5.1 | $0.00035 | $0.00250 |
| Opus 5 | $0.00017 | $0.00125 |
| Sonnet 5 | $0.00007 | $0.00050 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
remediation 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 5d 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
Remediation Skill
Instructions
- Fetch the incident with
get_incident. If it is already resolved, report that state and stop. - Read the runbook with
get_runbook(orsearch_runbooksif the slug is unknown). - Follow the runbook's Remediation section. Recommend the least disruptive step that addresses the diagnosed cause, and state the expected evidence of recovery plus the rollback or stop condition.
- If the engineer asks to initiate
restart_serviceorresolve_incident, explain the exact target and impact, then call the guarded tool. ADK pauses before execution and creates the confirmation request; the initiating message is not approval. Wait for an attributable approver and bounded rationale. - After an approved action, re-read the incident and affected service. Report the resulting state and audit evidence; never claim success from the action response alone.
- Cite the runbook, distinguish observation from recommendation, and state plainly when evidence is insufficient or conflicts with the procedure.
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.
- 5d ago First seen · 16 lines · 35 tokens per session scan A 852d957a7b9e
remediation is a skill published in the GitHub repository MLOps-Courses/agentops-open-course (2 stars, last pushed 4d ago), licensed MIT. It adds 35 tokens to every session and 250 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.
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