sddp-devops
Skill98 starsChanged 26 days agoMITView on GitHub
Create or refine the deployment and operations document. Direct command-bar dispatch only; do not select for general queries.
In this repository73 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- sddp-amendSkill
- sddp-analyzeSkill
- sddp-autopilotSkill
- sddp-checklistSkill
- sddp-clarifySkill
- sddp-devsetupSkill
- sddp-implement-qc-loopSkill
- sddp-implementSkill
- sddp-initSkill
- sddp-planSkill
- sddp-prdSkill
- sddp-projectplanSkill
- sddp-qcSkill
- sddp-regenSkill
- sddp-reverseengineerSkill
- sddp-specifySkill
- sddp-systemdesignSkill
- sddp-tasksSkill
- sddp-amendSkill
- sddp-analyzeSkill
- sddp-autopilotSkill
- sddp-checklistSkill
- sddp-clarifySkill
- sddp-devopsSkill
- sddp-devsetupSkill
- sddp-implement-qc-loopSkill
- sddp-implementSkill
- sddp-initSkill
- sddp-planSkill
- sddp-prdSkill
- sddp-projectplanSkill
- sddp-qcSkill
- sddp-regenSkill
- sddp-reverseengineerSkill
- sddp-specifySkill
- sddp-systemdesignSkill
- sddp-tasksSkill
- adr-authoringSkill
- artifact-conventionsSkill
- clarification-strategiesSkill
- compact-communicationSkill
- evidence-led-authoringSkill
- implementation-standardsSkill
- instructions-managementSkill
- markdown-compressionSkill
- plan-authoringSkill
- quality-assuranceSkill
- sdd-methodologySkill
- sddp-amendSkill
- sddp-analyzeSkill
- sddp-autopilotSkill
- sddp-checklistSkill
- sddp-clarifySkill
- sddp-devopsSkill
- sddp-devsetupSkill
- sddp-implement-qc-loopSkill
- sddp-implementSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 4 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 9
Create/refine canonical project-level deployment and operations context.
- Distinctive: line 16
When the shared workflow asks the user to choose or answer:
- Distinctive: line 17
Ask the user explicitly in chat and wait for the reply before continuing.
- Distinctive: line 20
Do not infer an answer from silence, partial output, or prior recommendations.
- Very specific: line 22
No ad hoc browsing. Only when the workflow says Delegate: Technical Researcher, read .github/agents/_technical-researcher.md and do only …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Argument hint: [project description, infrastructure context, deployment constraints, or operations inputs]
Command category: project-bootstrap
Prerequisites: none
Create/refine canonical project-level deployment and operations context. Ignore feature-level implementation detail; focus on deployment, infrastructure, observability, reliability, and operations.
Input
$ARGUMENTS = the user's message for this workflow. If none was provided, set $ARGUMENTS to empty and let the skill handle it.
Follow .github/sddp/workflows/deployment-operations/WORKFLOW.md.
When the shared workflow asks the user to choose or answer:
- Ask the user explicitly in chat and wait for the reply before continuing.
- Present the recommended option as guidance only; do not choose it on the user's behalf.
- Allow free-form answers anywhere the shared workflow allows them.
- Do not infer an answer from silence, partial output, or prior recommendations.
No ad hoc browsing. Only when the workflow says Delegate: Technical Researcher, read .github/agents/_technical-researcher.md and do only that delegated step.
Report progress at major milestones with completed and remaining work.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

