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 harness/harness-ai --skill manage-slosgit clone --depth 1 https://github.com/harness/harness-aiWrote 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/harness/harness-ai/manage-slos)<a href="https://agentmods.dev/skills/harness/harness-ai/manage-slos"><img src="https://agentmods.dev/badge/skills/harness/harness-ai/manage-slos/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/harness/harness-ai/manage-slos"><img src="https://agentmods.dev/badge/skills/harness/harness-ai/manage-slos.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 | $0.00133 | $0.01433 |
| Opus 5 | $0.00067 | $0.00717 |
| Sonnet 5 | $0.00027 | $0.00287 |
| Haiku 4.5 | $0.00013 | $0.00143 |
Grade A, and why
manage-slos 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 11d 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.
This is a copy
100% identical to manage-slos — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Manage SLOs / SRM
Limitation: The MCP server does not currently expose
slo,slo_alert, ormonitored_serviceresource types. SLO definitions, burn-rate alerts, and monitored-service configuration must be created and edited via the Harness UI under Service Reliability Management. This skill covers the parts of the SRM workflow that are supported via MCP: deployment correlation, on-call handover reports, and operational runbooks.
What this skill can do via MCP
| Workflow | Supported today |
|---|---|
| Define an SLO or SLI | ❌ Use the Harness UI |
| Configure error-budget / burn-rate alerts | ❌ Use the Harness UI |
| Configure a monitored service | ❌ Use the Harness UI |
| Correlate deployments with an incident | ✅ via execution |
| Summarize recent releases for on-call handover | ✅ via execution, service, environment |
| Draft an operational runbook | ✅ (LLM-authored; pulls context from MCP) |
Instructions
Step 1: Establish Scope
Call MCP tool: harness_list
Parameters:
resource_type: "project"
org_id: "<organization>"
Step 2: Incident Triage — Correlate Deployments
When the user reports an active incident:
- Identify the affected service and environment.
- Pull recent executions that deployed the service.
Call MCP tool: harness_list
Parameters:
resource_type: "execution"
org_id: "<organization>"
project_id: "<project>"
# filter by service or environment as needed
- Correlate incident start time with deployment timestamps.
- Pull the failing execution's details:
Call MCP tool: harness_get
Parameters:
resource_type: "execution"
resource_id: "<execution_id>"
org_id: "<organization>"
project_id: "<project>"
- Guide the user through structured RCA: blast radius, suspected root cause, mitigation steps, rollback candidate.
Step 3: On-Call Handover Report
Gather from the user: outgoing/incoming engineers, shift window, owned services.
Pull recent executions and services:
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.
- 11d ago First seen · 159 lines · 133 tokens per session scan A 1502bbc43770
manage-slos is a skill published in the GitHub repository harness/harness-ai (19 stars, last pushed 20d ago), licensed Apache-2.0. It adds 133 tokens to every session and 1,433 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to manage-slos, differing in 0 lines, and is treated as a copy.
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