Inference Autopilot
rednote-machine-learning/Inference-autopilot
Analyze, benchmark, diagnose, and optimize large-model inference deployments from hardware inventory, model details, workload traces, and latency or throughput SLOs.
Define and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting.
$ npx skills add wshobson/agents --skill slo-implementation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wshobson/agents slo-implementation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/wshobson/agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/observability-monitoring/skills/slo-implementation .claude/skills/slo-implementation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "slo-implementation" agent skill from https://github.com/wshobson/agents/tree/main/plugins/observability-monitoring/skills/slo-implementation into .claude/skills/slo-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slo-implementation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/wshobson/agents/tree/main/plugins/observability-monitoring/skills/slo-implementationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add wshobson/agents --skill slo-implementation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wshobson/agents slo-implementation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wshobson/agents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/observability-monitoring/skills/slo-implementation .agents/skills/slo-implementation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "slo-implementation" agent skill from https://github.com/wshobson/agents/tree/main/plugins/observability-monitoring/skills/slo-implementation into .agents/skills/slo-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slo-implementation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wshobson/agents --skill slo-implementation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wshobson/agents slo-implementation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wshobson/agents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/observability-monitoring/skills/slo-implementation .cursor/skills/slo-implementation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "slo-implementation" agent skill from https://github.com/wshobson/agents/tree/main/plugins/observability-monitoring/skills/slo-implementation into .cursor/skills/slo-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slo-implementation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/wshobson/agents.git --path plugins/observability-monitoring/skills/slo-implementation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add wshobson/agents --skill slo-implementation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wshobson/agents slo-implementation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wshobson/agents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/observability-monitoring/skills/slo-implementation .gemini/skills/slo-implementation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "slo-implementation" agent skill from https://github.com/wshobson/agents/tree/main/plugins/observability-monitoring/skills/slo-implementation into .gemini/skills/slo-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slo-implementation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install wshobson/agents slo-implementationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add wshobson/agents --skill slo-implementation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wshobson/agents.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/observability-monitoring/skills/slo-implementation .github/skills/slo-implementation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "slo-implementation" agent skill from https://github.com/wshobson/agents/tree/main/plugins/observability-monitoring/skills/slo-implementation into .github/skills/slo-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slo-implementation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add wshobson/agents --skill slo-implementation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wshobson/agents slo-implementation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wshobson/agents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/observability-monitoring/skills/slo-implementation .opencode/skills/slo-implementation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "slo-implementation" agent skill from https://github.com/wshobson/agents/tree/main/plugins/observability-monitoring/skills/slo-implementation into .opencode/skills/slo-implementation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slo-implementation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
slo-implementationDefine and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting.
Slo Implementation is an agent skill from wshobson/agents. Define and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting. Use when establishing reliability targets, implementing SRE practices, or measuring service performance.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/details.md`).
It sits in DevOps & Cloud, covering Site reliability engineering. The repository describes itself as: Multi-harness agentic plugin marketplace for Claude Code, Codex, Cursor, OpenCode, GitHub Copilot, Google Antigravity, and Pi. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 46891e7. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml and promql).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Slo Implementation loads about 1.7k tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 178 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from wshobson/agents at commit 46891e7, republished under its MIT licence (© wshobson). 178 words, ~1,681 tokens.
.claude/skills/slo-implementation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Framework for defining and implementing Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets.
Implement measurable reliability targets using SLIs, SLOs, and error budgets to balance reliability with innovation velocity.
SLA (Service Level Agreement)
↓ Contract with customers
SLO (Service Level Objective)
↓ Internal reliability target
SLI (Service Level Indicator)
↓ Actual measurement# Successful requests / Total requests
sum(rate(http_requests_total{status!~"5.."}[28d]))
/
sum(rate(http_requests_total[28d]))# Requests below latency threshold / Total requests
sum(rate(http_request_duration_seconds_bucket{le="0.5"}[28d]))
/
sum(rate(http_request_duration_seconds_count[28d]))# Successful writes / Total writes
sum(storage_writes_successful_total)
/
sum(storage_writes_total)| SLO % | Downtime/Month | Downtime/Year |
|---|---|---|
| 99% | 7.2 hours | 3.65 days |
| 99.9% | 43.2 minutes | 8.76 hours |
| 99.95% | 21.6 minutes | 4.38 hours |
| 99.99% | 4.32 minutes | 52.56 minutes |
Consider:
Example SLOs:
slos:
- name: api_availability
target: 99.9
window: 28d
sli: |
sum(rate(http_requests_total{status!~"5.."}[28d]))
/
sum(rate(http_requests_total[28d]))
- name: api_latency_p95
target: 99
window: 28d
sli: |
sum(rate(http_request_duration_seconds_bucket{le="0.5"}[28d]))
/
sum(rate(http_request_duration_seconds_count[28d]))Error Budget = 1 - SLO TargetExample:
error_budget_policy:
- remaining_budget: 100%
action: Normal development velocity
- remaining_budget: 50%
action: Consider postponing risky changes
- remaining_budget: 10%
action: Freeze non-critical changes
- remaining_budget: 0%
action: Feature freeze, focus on reliability# SLI Recording Rules
groups:
- name: sli_rules
interval: 30s
rules:
# Availability SLI
- record: sli:http_availability:ratio
expr: |
sum(rate(http_requests_total{status!~"5.."}[28d]))
/
sum(rate(http_requests_total[28d]))
# Latency SLI (requests < 500ms)
- record: sli:http_latency:ratio
expr: |
sum(rate(http_request_duration_seconds_bucket{le="0.5"}[28d]))
/
sum(rate(http_request_duration_seconds_count[28d]))
- name: slo_rules
interval: 5m
rules:
# SLO compliance (1 = meeting SLO, 0 = violating)
- record: slo:http_availability:compliance
expr: sli:http_availability:ratio >= bool 0.999
- record: slo:http_latency:compliance
expr: sli:http_latency:ratio >= bool 0.99
# Error budget remaining (percentage)
- record: slo:http_availability:error_budget_remaining
expr: |
(sli:http_availability:ratio - 0.999) / (1 - 0.999) * 100
# Error budget burn rate
- record: slo:http_availability:burn_rate_5m
expr: |
(1 - (
sum(rate(http_requests_total{status!~"5.."}[5m]))
/
sum(rate(http_requests_total[5m]))
)) / (1 - 0.999)groups:
- name: slo_alerts
interval: 1m
rules:
# Fast burn: 14.4x rate, 1 hour window
# Consumes 2% error budget in 1 hour
- alert: SLOErrorBudgetBurnFast
expr: |
slo:http_availability:burn_rate_1h > 14.4
and
slo:http_availability:burn_rate_5m > 14.4
for: 2m
labels:
severity: critical
annotations:
summary: "Fast error budget burn detected"
description: "Error budget burning at {{ $value }}x rate"
# Slow burn: 6x rate, 6 hour window
# Consumes 5% error budget in 6 hours
- alert: SLOErrorBudgetBurnSlow
expr: |
slo:http_availability:burn_rate_6h > 6
and
slo:http_availability:burn_rate_30m > 6
for: 15m
labels:
severity: warning
annotations:
summary: "Slow error budget burn detected"
description: "Error budget burning at {{ $value }}x rate"
# Error budget exhausted
- alert: SLOErrorBudgetExhausted
expr: slo:http_availability:error_budget_remaining < 0
for: 5m
labels:
severity: critical
annotations:
summary: "SLO error budget exhausted"
description: "Error budget remaining: {{ $value }}%"Grafana Dashboard Structure:
┌────────────────────────────────────┐
│ SLO Compliance (Current) │
│ ✓ 99.95% (Target: 99.9%) │
├────────────────────────────────────┤
│ Error Budget Remaining: 65% │
│ ████████░░ 65% │
├────────────────────────────────────┤
│ SLI Trend (28 days) │
│ [Time series graph] │
├────────────────────────────────────┤
│ Burn Rate Analysis │
│ [Burn rate by time window] │
└────────────────────────────────────┘Example Queries:
# Current SLO compliance
sli:http_availability:ratio * 100
# Error budget remaining
slo:http_availability:error_budget_remaining
# Days until error budget exhausted (at current burn rate)
(slo:http_availability:error_budget_remaining / 100)
*
28
/
(1 - sli:http_availability:ratio) * (1 - 0.999)More detailed templates and worked examples live in references/details.md. Read that file for the full pattern library.
© wshobson, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in plugins/observability-monitoring/skills/slo-implementation of wshobson/agents.
Open the folder on GitHubat commit 46891e7
We found 28 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 10 other GitHub owners. This page covers the copy in wshobson/agents, which our catalogue first saw on October 7, 2026.
Slo Implementation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Slo Implementation this skillwshobson/agents | 40k | 10 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Inference Autopilotrednote-machine-learning/Inference-autopilot | 142 | — | ~4.5k | Automated safety check: Pass | Apache-2.0 | |
| Executing Distributed System Testsshenli/distributed-system-testing | 231 | — | ~5.1k | Automated safety check: Notes | MIT | |
| Alerting Irmgrafana/skills | 278 | 1 repos | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Agentforce D360 Analyzeforcedotcom/sf-skills | 1.1k | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Promqlgrafana/skills | 278 | 1 repos | ~1.1k | Automated safety check: Pass | Apache-2.0 |
rednote-machine-learning/Inference-autopilot
Analyze, benchmark, diagnose, and optimize large-model inference deployments from hardware inventory, model details, workload traces, and latency or throughput SLOs.
shenli/distributed-system-testing
A skill your agent uses when running a previously designed distributed-systems test plan against a real or simulated cluster — driving fault injection, workload, chaos scenarios, linearizability /…
grafana/skills
Configure Grafana Alerting, Incident Response Management (IRM), and SLOs end-to-end — provisions Grafana-managed and data-source-managed alert rules, contact points (Slack/PagerDuty/email/webhook)…
forcedotcom/sf-skills
Data Cloud 360° view of a single Agentforce session. An agent skill from forcedotcom/sf-skills.
grafana/skills
Write, validate, and optimize PromQL for Prometheus / Grafana Mimir / Grafana Cloud Metrics.
2SSK/dot-files
Observability best practices. An agent skill from 2SSK/dot-files.
wshobson/agents
Cuts cloud spend across AWS, Azure, GCP and OCI with cost tagging, rightsizing, commitment and spot pricing models, and architecture changes.
wshobson/agents
Covers building subscription billing: billing cycles, subscription states, invoice generation, proration, tax handling and dunning for failed payments.
wshobson/agents
Profiles slow Python code with cProfile and memory profilers, then applies targeted fixes for CPU, memory, I/O and query bottlenecks.
wshobson/agents
Covers portfolio risk measurement with VaR, CVaR, Sharpe, Sortino and drawdown, plus guidance on limits, stress tests and tail risk.
wshobson/agents
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wshobson/agents
Writes unit tests for shell scripts with Bats: error-condition tests, fixtures and mocks, cross-shell checks, parallel runs, helper files and CI integration.
Categories
Define and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting. Slo Implementation is an agent skill from wshobson/agents. Define and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting.
Slo Implementation fits situations like: establishing reliability targets; implementing SRE practices; measuring service performance.
Run `npx skills add wshobson/agents --skill slo-implementation -a claude-code`. Or copy the skill folder (plugins/observability-monitoring/skills/slo-implementation in wshobson/agents) into .claude/skills/slo-implementation in your project. Claude Code loads it when a task matches its description.
Run `npx skills add wshobson/agents --skill slo-implementation -a codex`. Or copy the skill folder (plugins/observability-monitoring/skills/slo-implementation in wshobson/agents) into .agents/skills/slo-implementation in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wshobson/agents --skill slo-implementation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/slo-implementation, .gemini/skills/slo-implementation, .github/skills/slo-implementation and .opencode/skills/slo-implementation in your project.
SKILL.md names no scripts, command-line tools or credentials: Slo Implementation is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Slo Implementation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 345 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Slo Implementation: Inference Autopilot (rednote-machine-learning/Inference-autopilot, 142 stars), Executing Distributed System Tests (shenli/distributed-system-testing, 231 stars), Alerting Irm (grafana/skills, 278 stars) and Agentforce D360 Analyze (forcedotcom/sf-skills, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
wshobson (a GitHub user) maintains it in wshobson/agents, which has 40,254 GitHub stars. The repository holds 142 skills in this directory. The repository was last updated on October 5, 2026.
Source: wshobson/agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.