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Fortimanager Ops

Community
automateyournetwork
fortimanager-ops

FortiManager policy operations — ADOM inventory, policy package review, recursive object resolution, revision history, install preview, and gated package install. Use when auditing FortiGate firewall policy at the MANAGER level (intent), reviewing ADOM policy packages, or planning a package install with rollback context.

Overview

Publisherautomateyournetwork
Repositorynetclaw
Skill namefortimanager-ops
Stars
680
Forks
189
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Fortimanager Ops 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/automateyournetwork/netclaw/tree/main/workspace/skills/fortimanager-ops
  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/automateyournetwork/netclaw.git /tmp/netclaw
mkdir -p .claude/skills
cp -r /tmp/netclaw/workspace/skills/fortimanager-ops .claude/skills/fortimanager-ops
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fortimanager Ops 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 Fortimanager Ops 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 Fortimanager Ops 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.

FortiManager Operations — the manager plane

MCP Server

  • Server: fortinet-mcp (NetClaw-authored, spec 080 / roadmap R3)
  • Command: $FORTINET_MCP_CMD
  • Transport: stdio
  • Requires: FORTIMANAGER_HOST, FORTIMANAGER_API_TOKEN
  • Mode: read-only by default; installs require two gates (below)

v2.0.0: this skill previously declared FORTIMANAGER_MCP_CMD pointing at jmpijll/fortimanager-mcp, which was never vendored, never registered and not installable — the skill was a claim with no server behind it. It is now backed by fortinet-mcp, and the command variable changed to FORTINET_MCP_CMD because one server serves all three Fortinet planes.

The distinction this skill exists to protect

FortiManager holds INTENT. It does not know what a device is actually doing.

QuestionPlaneSkill
"What policy is supposed to apply here?"managerthis skill
"What is the box actually running? Is the tunnel up?"devicefortigate-ops
"Has anything ever matched this rule?"analyzerfortianalyzer-ops
"Run a raw FortiOS CLI command"CLImultivendor-raw-cli (spec 076)

A policy package and a FortiGate's running config legitimately diverge between installs. That gap is where drift, unauthorised change and failed installs live — use fgt_compare_with_manager to surface it rather than assuming they agree.

Tools (8 read-only + 2 write)

ToolWhat it answers
fmg_list_adomsWhich ADOMs exist. The ADOM scopes everything else
fmg_list_devicesManaged FortiGates, connection and sync status
fmg_list_policy_packagesPackages in an ADOM and their install targets
fmg_get_policy_packageOrdered rules: position, action, enabled state
fmg_search_rulesRules matching a source, destination, service or object
fmg_resolve_objectObject/group → members, resolved recursively
fmg_get_revisionsRevision history — rollback context
fmg_preview_installWhat an install would change. No gate required
fmg_check_change_recordIs a ServiceNow CR approved? Read-only
fmg_install_packageProduction change. Two gates, see below

Every response carries its plane and scope

jsonc
{ "plane": "manager", "scope": {"adom": "root", "package": "Corp"},
  "source": "...", "outcome": "ok", "data": {...}, "notes": [] }

outcome distinguishes results that look alike: ok, empty_result, plane_unreachable, auth_expired, auth_missing, scope_indeterminate, and the three separate write refusals. An expired session is auth_expired, never "no policies exist" — that would be a silent, plausible, wrong answer.

Workflow: policy package audit

  1. fmg_list_adoms → pick the ADOM. A package name is unique only within one.
  2. fmg_list_policy_packages → find the package and its install targets.
  3. fmg_get_policy_package → ordered rules. Note position: shadowing is positional.
  4. fmg_resolve_object on every group a rule references. A rule reported only by object name is not an audit — "allow GRP_CORP to GRP_DMZ" says nothing about which addresses that permits.
  5. fmg_get_revisions → rollback context before proposing any change.
  6. Feed the rules to fwrule-analyzer for overlap, shadowing and conflict analysis.

Workflow: is intent matching reality?

  1. fmg_get_policy_package — the intent.
  2. fgt_compare_with_manager (in fortigate-ops) — the divergence.
  3. only_in_device entries are candidate out-of-band changes: someone edited the firewall directly. This is the single most valuable finding here.
  4. only_in_manager usually means the package has not been installed since those rules were added — check fmg_list_devices sync status.

Writes: two gates, and neither substitutes for the other

fmg_install_package pushes policy to production firewalls — the highest blast-radius action available here.

ConditionOutcome
FORTINET_ALLOW_WRITES not setrefused_read_only
No approved_byrefused_no_approval
No approved ServiceNow CR (non-lab)refused_no_change_record
Both presentproceeds: revision identified → install → verify

Human approval and a ServiceNow change record are different gates. A CR does not imply a human said yes; a human saying yes does not imply change control approved it. Lab devices waive the CR gate only — never the approval gate — and a device that cannot be classified is treated as production.

Always run fmg_preview_install first. It shows what would change and needs no gate.

Integration with other skills

SkillHow they compose
fortigate-opsDevice-plane state; fgt_compare_with_manager for drift
fortianalyzer-opsWhether a rule has actually matched traffic
fwrule-analyzerFeed retrieved policy to its FortiOS parser for overlap/shadowing
servicenow-change-workflowSupplies the CR that satisfies gate 2 of fmg_install_package
multivendor-raw-cliRaw FortiOS CLI (spec 076) — a different plane, not a substitute
gait-session-trackingEvery operation here is GAIT-audited automatically

Important rules

  • Treat package install as production change execution — baseline, verify, rollback.
  • Always name the ADOM. A package without one is ambiguous.
  • Resolve objects before drawing conclusions.
  • Never present manager intent as observed device state.
  • An empty result is not an error, and auth_expired is not "no data".

Frequently asked questions

What does the Fortimanager Ops AI skill do?

FortiManager policy operations — ADOM inventory, policy package review, recursive object resolution, revision history, install preview, and gated package install. Use when auditing FortiGate firewall policy at the MANAGER level (intent), reviewing ADOM policy packages, or planning a package install with rollback context.

Why use Fortimanager Ops on TypingMind?

Because you install it once and use it with any model. Fortimanager Ops 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 Fortimanager Ops in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/fortimanager-ops. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Fortimanager Ops?

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 Fortimanager Ops?

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

Is the Fortimanager Ops AI skill free?

Yes. It is published on GitHub by automateyournetwork under the Apache-2.0 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.

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