Oci Functions Troubleshoot logo

Oci Functions Troubleshoot

Organization
oracle
oci-functions-troubleshoot

Diagnose OCI Functions setup, control-plane, deployment, invocation, and observability issues using a deterministic triage workflow. Use when asked to classify Fn CLI errors, deploy or invoke failures, OCIR auth and registry issues, app-limit symptoms, logs, tracing, metrics, or limits. Diagnose first, prefer read-only checks, and do not execute fixes unless the user explicitly asks.

Overview

Publisheroracle
Repositoryskills
Skill nameoci-functions-troubleshoot
Stars
879
Forks
251
Bundled files
8
LicenseUPL-1.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by oracle on GitHub. Read the source before you install it.

Installation

Install the Oci Functions Troubleshoot AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/oracle/skills/tree/main/oci/functions/oci-functions-troubleshoot
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/oracle/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/oci/functions/oci-functions-troubleshoot .claude/skills/oci-functions-troubleshoot
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Oci Functions Troubleshoot in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Oci Functions Troubleshoot on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Oci Functions Troubleshoot is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OCI Function Troubleshoot

Use this skill to isolate the most likely cause of an OCI Functions problem from error text, command output, or observability signals.

This skill is diagnosis-first and non-mutating by default:

  • prefer read-only checks
  • do not edit Fn context, log into Docker, create or update apps, redeploy, or change infrastructure unless the user explicitly asks to execute a fix
  • if the user wants the fix executed, finish the diagnosis first and hand off mutating remediation to $oci-functions-deploy

Output Contract

Always answer in this exact shape:

  • stage: one of setup_or_control_plane, create, deploy, invoke, observability_first
  • evidence: 1-3 concrete facts from the user's error text, command, config, logs, metrics, or limits
  • most_likely_cause: one primary cause, or a ranked top-2 shortlist when confidence is low
  • confidence: low, medium, or high
  • next_confirming_check: the single best read-only check to narrow or confirm the cause
  • smallest_safe_remediation: the least invasive next action; if evidence is weak, this can be "collect more evidence with ..."
  • validation: the follow-up step that proves the remediation worked

Triage

  1. If the user provides an exact error string, start with references/error-patterns.md.
  2. Classify the issue from the failed action:
  • setup_or_control_plane: local Fn/OCI/OCIR/tooling/auth/context/policy problems before normal app or function operations succeed
  • create: application creation failures
  • deploy: fn deploy, image build or push, func.yaml, app config, subnet annotation, or registry-target failures
  • invoke: runtime invocation, HTTP, image pull, timeout, memory, networking, detached delivery, or response-limit failures after a function has been deployed
  • observability_first: the user starts from logs, traces, metrics, limits, or "why is this function unhealthy?"
  1. If the stage is ambiguous:
  • ask exactly one disambiguating question when a single missing fact would change the stage
  • otherwise present the top 2 plausible stages in ranked order and continue with the best read-only confirming check

Minimum Facts

Capture the minimum facts before diagnosing:

  • exact error text and HTTP status if present
  • command or action that failed
  • region, compartment/profile, app name, and function name if known
  • whether the problem is local, deploy-time, invoke-time, or telemetry-first
  • whether Fn CLI, OCI CLI, Docker, Logging, Monitoring, and Tracing access are available

Preferred Read-Only Checks

Prefer non-mutating checks when tooling is available:

  • fn inspect context
  • fn list apps
  • fn inspect app <app-name>
  • fn inspect function <app-name> <function-name>
  • read local func.yaml
  • inspect environment values that can override expected behavior, especially FN_REGISTRY
  • read logs, traces, metrics, and limits before recommending edits
  • use DEBUG=1 or OCI_GO_SDK_DEBUG=v only for additional diagnostic signal, not as a first fix

If tools or access are missing, stay docs-first:

  • classify the failure from the error text
  • use the phase reference file for likely causes
  • use references/error-patterns.md when the text is the strongest clue

Workflow

Setup Or Control Plane

Use references/setup-and-runtime.md for:

  • Fn CLI 401 and 404
  • OCI key, passphrase, and private key format problems
  • wrong region, compartment, endpoint, or app/function target
  • IAM, policy, dynamic-group, or network-resource authorization failures
  • Docker registry unauthorized failures
  • stale or outdated CLI behavior

Start with read-only checks:

  • inspect active Fn context values
  • verify the intended OCI profile, compartment, and region match the failing target
  • confirm the registry host derived from the context
  • for 404, separate endpoint or name mismatches from IAM/policy or compartment-targeting issues before suggesting reconfiguration

Application Creation

Use references/create.md for create-time failures.

Focus on:

  • documented service-limit style failures such as maximum application count
  • whether the request is going to the intended compartment and region
  • whether IAM or compartment targeting is wrong when the error is not clearly limit-shaped
  • whether the smallest safe path is reuse, cleanup, or a limit increase request

Deployment

Use references/deploy.md for:

  • fn deploy failures
  • image build, push, or registry auth problems
  • func.yaml schema issues
  • wrong application context or missing subnet annotations
  • architecture mismatch symptoms
  • identity-domain or federated OCIR username issues

Check in this order:

  • active Fn context and target app
  • local func.yaml
  • effective registry target, including FN_REGISTRY
  • app annotations and subnet/network assumptions
  • whether the failure is local build, image push, or service-side deploy
  • fn version when architecture or stale-client symptoms are plausible

Invocation

Use references/invoke.md for:

  • request or response size limits
  • throttling, detached delivery, or event-triggered retries
  • client disconnect, image pull, DNS, timeout, memory, syslog, security-attribute, or dynamic-group failures
  • subnet, DHCP, resolver, or service-availability failures

Check in this order:

  • exact HTTP code and service error text
  • whether the error happens before code starts, during init, during execution, or after execution but before delivery completes
  • logs first for code/runtime clues when available
  • traces next when enabled and downstream timing or dependency timing is unclear
  • metrics next for error rate, latency, concurrency, and invoke-type trends
  • limits last when the symptom suggests capacity pressure or service ceilings

Observability First

Use references/observability.md when the user starts from symptoms instead of a single failing command.

Default observability sequence:

  1. Logs: determine whether the function ran and whether application logging is enabled
  2. Tracing: use traces when enabled and the missing clue is dependency timing, latency, or call path
  3. Metrics: distinguish execution failure, throttling, detached delivery, latency, and capacity pressure
  4. Limits: confirm whether create or invoke failures align with service limits
  5. Debug flags: use DEBUG=1 or OCI_GO_SDK_DEBUG=v only when reproducing locally or when request/SDK details are still missing

Reference Map

  • setup/control-plane issues: references/setup-and-runtime.md
  • app creation issues: references/create.md
  • deployment issues: references/deploy.md
  • invocation issues: references/invoke.md
  • logs, traces, metrics, limits, debug flags: references/observability.md
  • exact strings to likely causes: references/error-patterns.md
  • reusable prompt patterns: references/example-prompts.md

Guardrails

  • Diagnose and isolate first. Do not mutate local context, Docker auth, app config, deployed state, or infrastructure unless the user explicitly asks to execute a fix.
  • If the user asks to execute the fix, complete the diagnosis summary first and hand off mutating repair work to $oci-functions-deploy.
  • Do not start with mutating fixes when a read-only check can narrow the cause.
  • Do not assume a 404 is only an endpoint or name problem; treat IAM, policy, compartment targeting, dynamic groups, and network-resource authorization as first-class alternatives.
  • Do not assume a deploy issue is code-related until registry, app, client version, and network context are checked.
  • Do not assume an invoke issue is platform-related until logs, traces, and metrics are checked.
  • Treat FN_REGISTRY, active Fn context, app annotations, tracing availability, and service limits as common hidden causes.
  • If the user gives only a partial symptom, ask for the exact error text or failing command before escalating to broad remediation.
  • When evidence is partial, prefer a ranked shortlist of plausible causes over a single overconfident root cause.

Sources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Oci Functions Troubleshoot AI skill do?

Diagnose OCI Functions setup, control-plane, deployment, invocation, and observability issues using a deterministic triage workflow. Use when asked to classify Fn CLI errors, deploy or invoke failures, OCIR auth and registry issues, app-limit symptoms, logs, tracing, metrics, or limits. Diagnose first, prefer read-only checks, and do not execute fixes unless the user explicitly asks.

Why use Oci Functions Troubleshoot on TypingMind?

Because you install it once and use it with any model. Oci Functions Troubleshoot is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Oci Functions Troubleshoot in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oracle/skills/tree/main/oci/functions/oci-functions-troubleshoot. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Oci Functions Troubleshoot?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Oci Functions Troubleshoot?

As many as you like. As long as a model supports skills, you can use Oci Functions Troubleshoot with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Oci Functions Troubleshoot AI skill free?

Yes. It is published on GitHub by oracle under the UPL-1.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇