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 incident-responsegit 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/incident-response)<a href="https://agentmods.dev/skills/harness/harness-ai/incident-response"><img src="https://agentmods.dev/badge/skills/harness/harness-ai/incident-response/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/incident-response"><img src="https://agentmods.dev/badge/skills/harness/harness-ai/incident-response.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 | $0.00122 | $0.01427 |
| Opus 5 | $0.00061 | $0.00714 |
| Sonnet 5 | $0.00024 | $0.00285 |
| Haiku 4.5 | $0.00012 | $0.00143 |
Grade A, and why
incident-response 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 9d 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 incident-response — 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Response
Correlate incidents with deployments, assess blast radius, and generate postmortem documents using Harness MCP.
Instructions
Step 1: Establish Scope
Confirm the affected service, environment, and incident details.
Call MCP tool: harness_list
Parameters:
resource_type: "service"
org_id: "<organization>"
project_id: "<project>"
Step 2: Identify the Incident Response Task
Determine which workflow the user needs:
- Deployment-to-Incident Correlation -- Determine if a recent deployment caused the incident
- Blast Radius Assessment -- Map affected services and downstream impact
- Postmortem Generation -- Create a structured postmortem document
Step 3: Correlate Deployment to Incident
Gather from the user:
- Affected service name and environment
- Alert or incident name and start time
- Observed symptoms (error rate spike, latency, outage)
Pull recent deployments:
Call MCP tool: harness_list
Parameters:
resource_type: "execution"
org_id: "<organization>"
project_id: "<project>"
status: "Success"
For each recent deployment, check:
- Timing: Was the deployment within the incident correlation window (e.g., 2 hours before)?
- Service match: Does the deployed service match or depend on the affected service?
- Change content: What changed in the deployment (config, code, infrastructure)?
Build a deployment timeline:
- List all deployments to the affected environment in the last N hours
- Mark the incident start time on the timeline
- Identify the most likely causal deployment (closest before incident start)
- Check if a rollback was performed and whether it resolved the issue
Present findings with confidence level: HIGH (deployment matches timing + service), MEDIUM (timing matches but different service), LOW (no deployment correlation found).
Step 4: Assess Blast Radius
Gather from the user:
- Failing service and failure type (outage, elevated error rate, high latency)
- Current error rate or severity
- Environment
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.
- 9d ago First seen · 176 lines · 122 tokens per session scan A 7eb5985478d5
incident-response is a skill published in the GitHub repository harness/harness-ai (19 stars, last pushed 18d ago), licensed Apache-2.0. It adds 122 tokens to every session and 1,427 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to incident-response, differing in 0 lines, and is treated as a copy.
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