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Catc Inventory

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automateyournetwork
catc-inventory

Catalyst Center device inventory and site management - list/filter devices by hostname, IP, platform, family, role, reachability; view site hierarchy; get interface details per device; device reachability monitoring; cross-reference with pyATS. Use when listing network devices, checking device reachability, auditing software versions, viewing site hierarchy, or finding a device by serial number. This is a narrow, purpose-built tool for that pyATS cross-reference workflow specifically. For anything else in Catalyst Center (wireless, assurance health, compliance, software images, events) or a comprehensive read-only query, use `catalyst-center-readonly` instead.

Overview

Publisherautomateyournetwork
Repositorynetclaw
Skill namecatc-inventory
Stars
680
Forks
189
Bundled files
Instructions only
LicenseApache-2.0
Links
Skill sourceRepository
  • 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 Catc Inventory 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/catc-inventory
  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/catc-inventory .claude/skills/catc-inventory
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Catc Inventory 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 Catc Inventory 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 Catc Inventory 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.

Catalyst Center Device Inventory and Site Management

Catalyst Center MCP Server

All Catalyst Center tool calls use this invocation pattern:

CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 -u $CATC_MCP_SCRIPT

Variable shorthand used throughout this document:

CATC_CMD="CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 -u $CATC_MCP_SCRIPT"

How to Call Tools

Use the $MCP_CALL protocol handler to invoke MCP tools:

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" TOOL_NAME 'ARGS_JSON'

When to Use

  • Asset inventory audits and device lifecycle management
  • Verifying device reachability across the campus or data center
  • Site hierarchy reviews before provisioning changes
  • Pre-change baseline: confirm which devices are at a given site
  • Interface-level capacity planning and port utilization analysis
  • Cross-referencing Catalyst Center inventory with pyATS testbed data
  • Compliance checks: platform IDs, software versions, device roles

Available Inventory Tools

1. fetch_devices -- List and Filter Network Devices

Fetches devices from the /dna/intent/api/v1/network-device endpoint with extensive filtering. NEVER call this tool without at least one filter parameter -- unfiltered queries can return massive result sets and are blocked by design.

Parameters (all optional, but at least one required):

ParameterTypeDescription
hostnameList[str]Filter by device hostname(s)
managementIpAddressList[str]Filter by management IP(s)
serialNumberList[str]Filter by serial number(s)
platformIdList[str]Filter by platform ID (e.g., C9300-48UXM)
familyList[str]Filter by device family (e.g., Switches and Hubs, Routers, Wireless Controller)
typeList[str]Filter by device type (e.g., Cisco Catalyst 9300 Switch)
roleList[str]Filter by role: ACCESS, DISTRIBUTION, CORE, BORDER ROUTER, UNKNOWN
reachabilityStatusList[str]Filter by: Reachable, Unreachable
collectionStatusList[str]Filter by: Managed, Partial Collection Failure, Could Not Synchronize
softwareVersionList[str]Filter by IOS/NX-OS version string
softwareTypeList[str]Filter by: IOS-XE, NX-OS, IOS, AireOS
seriesList[str]Filter by product series (e.g., Cisco Catalyst 9300 Series Switches)
locationNameList[str]Filter by full site path (e.g., Global/USA/Building1/Floor1)
associatedWlcIpList[str]For APs: filter by WLC management IP
macAddressList[str]Filter by device MAC address(es)
idList[str]Filter by device UUID(s)
roleSourceList[str]Filter by role source: MANUAL, AUTO
offsetstrStarting record for pagination (e.g., "0")
limitstrMaximum records to return (e.g., "50")
sortBystrAttribute to sort by (e.g., hostname)
sortOrderstrasc or desc

Response fields per device: id (UUID), hostname, managementIpAddress, macAddress, serialNumber, platformId, softwareVersion, softwareType, type, family, series, role, roleSource, reachabilityStatus, collectionStatus, errorCode, locationName, location, upTime, lastUpdated, lastUpdateTime, associatedWlcIp, apManagerInterfaceIp, and more.

2. fetch_sites -- List All Sites

Fetches the complete site hierarchy from Catalyst Center. Takes no arguments.

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_sites '{}'

Response fields per site: id, name, parentId, siteNameHierarchy (full path like Global/USA/NYC/Floor2), type (area, building, floor), address, latitude, longitude.

3. fetch_interfaces -- Get Interfaces for a Device

Fetches all interfaces for a specific device by its UUID from the /dna/intent/api/v1/interface/network-device/{device_id} endpoint.

Parameters:

  • device_id (string, required): The UUID of the device (obtained from fetch_devices response id field)
bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_interfaces '{"device_id":"a1b2c3d4-e5f6-7890-abcd-ef1234567890"}'

Response fields per interface: id, deviceId, portName, interfaceType, adminStatus, status (operStatus), speed, duplex, ipv4Address, ipv4Mask, macAddress, mediaType, mtu, vlanId, nativeVlanId, description, portMode, lastUpdated, and more.

Inventory Workflows

Workflow 1: Find All Unreachable Devices

Identify devices that Catalyst Center cannot reach -- critical for outage detection.

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"reachabilityStatus":["Unreachable"]}'

Analyze the results:

  • Record each unreachable device: hostname, management IP, platformId, locationName
  • Check lastUpdated to determine when the device was last seen
  • Check collectionStatus for additional context (Could Not Synchronize vs Partial Collection Failure)
  • Group by locationName to determine if the outage is site-localized

Escalation: If multiple devices at the same site are unreachable, this likely indicates a site-wide outage (WAN link, upstream switch, power). Escalate to the site-wide outage triage workflow in the catc-troubleshoot skill.

Workflow 2: List All Switches

Enumerate all switching devices managed by Catalyst Center.

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"family":["Switches and Hubs"]}'

Refine by role:

bash
# Access layer switches only
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"family":["Switches and Hubs"],"role":["ACCESS"]}'

# Distribution layer switches
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"family":["Switches and Hubs"],"role":["DISTRIBUTION"]}'

# Core switches
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"family":["Switches and Hubs"],"role":["CORE"]}'

Refine by platform:

bash
# All Catalyst 9300 series
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"series":["Cisco Catalyst 9300 Series Switches"]}'

# Specific platform ID
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"platformId":["C9300-48UXM"]}'

Workflow 3: List All Routers

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"family":["Routers"]}'

Workflow 4: List Wireless Controllers and Access Points

bash
# Wireless LAN Controllers
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"family":["Wireless Controller"]}'

# Unified Access Points
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"family":["Unified AP"]}'

# APs associated with a specific WLC
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"associatedWlcIp":["10.1.100.10"]}'

Workflow 5: Get Interfaces for a Specific Device

This is a two-step process: first find the device to obtain its UUID, then query interfaces.

Step 1: Find the device

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"hostname":["CORE-SW-01"]}'

Extract the id field (UUID) from the response.

Step 2: Fetch interfaces using the UUID

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_interfaces '{"device_id":"a1b2c3d4-e5f6-7890-abcd-ef1234567890"}'

Analyze interface data:

  • Count interfaces by adminStatus (UP vs DOWN) and status (operationally UP vs DOWN)
  • Identify interfaces with adminStatus=UP but status=down -- these are operationally failed interfaces
  • Check speed and duplex for mismatches
  • Identify trunk ports vs access ports via portMode
  • Calculate port utilization: (used ports / total ports) * 100

Workflow 6: Site-Based Device Grouping

Build a report of devices organized by site hierarchy.

Step 1: Retrieve the site hierarchy

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_sites '{}'

Step 2: For each site, retrieve devices at that location

bash
# Devices at a specific site
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"locationName":["Global/USA/NYC/Floor2"]}'

Build the report:

Site Inventory Report
=====================
Catalyst Center: $CCC_HOST
Timestamp: YYYY-MM-DD HH:MM UTC

Global/USA/NYC
  Global/USA/NYC/Floor1 (floor)
    +--------------+------------------+-----------+------------+--------+
    | Hostname     | Mgmt IP          | Platform  | SW Version | Status |
    +--------------+------------------+-----------+------------+--------+
    | ACC-SW-01    | 10.1.10.1        | C9300-48U | 17.09.04a  | Reach  |
    | ACC-SW-02    | 10.1.10.2        | C9300-48U | 17.09.04a  | Reach  |
    | AP-NYC-F1-01 | 10.1.10.100      | C9120AXI  | 17.09.04a  | Reach  |
    +--------------+------------------+-----------+------------+--------+

  Global/USA/NYC/Floor2 (floor)
    +--------------+------------------+-----------+------------+--------+
    | Hostname     | Mgmt IP          | Platform  | SW Version | Status |
    +--------------+------------------+-----------+------------+--------+
    | ACC-SW-03    | 10.1.20.1        | C9300-24P | 17.09.04a  | Reach  |
    | AP-NYC-F2-01 | 10.1.20.100      | C9130AXI  | 17.09.04a  | Unrch  |
    +--------------+------------------+-----------+------------+--------+

Total: 5 devices | 4 reachable | 1 unreachable

Workflow 7: Software Version Audit

Identify devices running non-compliant or mixed firmware versions.

bash
# Find all devices on a specific software version
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"softwareVersion":["17.09.04a"]}'

# Find devices running IOS-XE
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"softwareType":["IOS-XE"]}'

Audit steps:

  1. Query each device family separately (switches, routers, WLCs, APs)
  2. Group results by softwareVersion
  3. Flag devices not on the approved golden image version
  4. Report version distribution per platform:
Software Version Audit
======================
Platform: Cisco Catalyst 9300 Series Switches
  17.09.04a: 42 devices (APPROVED)
  17.06.05 : 3 devices  (NON-COMPLIANT -- schedule upgrade)
  17.03.04a: 1 device   (EOL VERSION -- immediate upgrade required)

Platform: Cisco Catalyst 9800 Wireless Controller
  17.09.04a: 2 devices (APPROVED)

Workflow 8: Find a Device by Serial Number or IP

bash
# By serial number
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"serialNumber":["FDO2325A0B1"]}'

# By management IP
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"managementIpAddress":["10.1.10.1"]}'

# By MAC address
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"macAddress":["00:1A:2B:3C:4D:5E"]}'

Workflow 9: Collection Failure Investigation

Devices with collection failures may have partial data in Catalyst Center.

bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"collectionStatus":["Partial Collection Failure"]}'
bash
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"collectionStatus":["Could Not Synchronize"]}'

Common causes:

  • SNMP community/credential mismatch
  • NETCONF/RESTCONF not enabled on the device
  • SSH connectivity issue (ACL blocking, timeout)
  • Device CPU too high to respond to polling
  • Device running an unsupported software version

Cross-Reference: Catalyst Center + pyATS

When the pyATS testbed is available ($PYATS_MCP_SCRIPT and $PYATS_TESTBED_PATH are set), cross-reference Catalyst Center inventory with live device data for deeper validation.

Verify Device Software Version

Compare what Catalyst Center reports vs what the device itself reports:

bash
# Catalyst Center says the device runs 17.09.04a
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_devices '{"hostname":["CORE-SW-01"]}'

# Verify directly from the device
PYATS_TESTBED_PATH=$PYATS_TESTBED_PATH python3 $MCP_CALL "${PYATS_PYTHON:-python3} -u $PYATS_MCP_SCRIPT" pyats_run_show_command '{"device_name":"CORE-SW-01","command":"show version"}'

Flag any discrepancy -- this indicates Catalyst Center inventory is stale and needs a resync.

Verify Interface State

Compare Catalyst Center interface data vs live device state:

bash
# Catalyst Center interface data (may be up to 25 minutes stale)
CCC_HOST=$CCC_HOST CCC_USER=$CCC_USER CCC_PWD=$CCC_PWD python3 $MCP_CALL "python3 -u $CATC_MCP_SCRIPT" fetch_interfaces '{"device_id":"<UUID>"}'

# Live interface state from the device
PYATS_TESTBED_PATH=$PYATS_TESTBED_PATH python3 $MCP_CALL "${PYATS_PYTHON:-python3} -u $PYATS_MCP_SCRIPT" pyats_run_show_command '{"device_name":"CORE-SW-01","command":"show ip interface brief"}'

Identify drift: Interfaces that show UP in Catalyst Center but DOWN on the live device (or vice versa) indicate a polling lag or inventory desync.

Inventory Report Format

Always produce a consolidated inventory summary when performing audit workflows:

Catalyst Center Inventory Report
=================================
Controller: $CCC_HOST
Timestamp: YYYY-MM-DD HH:MM UTC

Device Summary
--------------
Total Devices: 156
  Switches and Hubs: 92 (59%)
  Routers: 12 (8%)
  Wireless Controller: 4 (3%)
  Unified AP: 48 (31%)

Reachability
------------
  Reachable: 152 (97.4%)
  Unreachable: 4 (2.6%)
    - ACC-SW-15 (10.1.30.15) at Global/USA/NYC/Floor3 -- last seen 2h ago
    - AP-CHI-F2-03 (10.2.20.103) at Global/USA/CHI/Floor2 -- last seen 45m ago
    - AP-CHI-F2-04 (10.2.20.104) at Global/USA/CHI/Floor2 -- last seen 45m ago
    - RTR-WAN-02 (10.0.0.2) at Global/USA/NYC/MDF -- last seen 6h ago

Collection Status
-----------------
  Managed: 150
  Partial Collection Failure: 4
  Could Not Synchronize: 2

Role Distribution
-----------------
  ACCESS: 82 | DISTRIBUTION: 8 | CORE: 4 | BORDER ROUTER: 2 | UNKNOWN: 12

Site Summary
------------
Total Sites: 24 (8 areas, 10 buildings, 6 floors)
Sites with unreachable devices: 2 (Global/USA/NYC/Floor3, Global/USA/CHI/Floor2)

Software Version Compliance
----------------------------
  IOS-XE 17.09.04a: 140 devices (COMPLIANT)
  IOS-XE 17.06.05:  8 devices  (NON-COMPLIANT)
  AireOS 8.10.185:  4 devices  (COMPLIANT)
  NX-OS 10.3(2):    4 devices  (COMPLIANT)

GAIT Audit Trail

After completing any inventory operation, record the session in GAIT:

bash
python3 $MCP_CALL "python3 -u $GAIT_MCP_SCRIPT" gait_record_turn '{"user_text":"Example only: replace with the actual authorized request.","assistant_text":"Catalyst Center inventory audit on $CCC_HOST: 156 devices total, 152 reachable (97.4%), 4 unreachable (ACC-SW-15, AP-CHI-F2-03, AP-CHI-F2-04, RTR-WAN-02). Collection failures: 6 devices. Software compliance: 96% on approved versions. 2 sites with unreachable devices flagged for investigation.","artifacts":[]}'

Audit examples are illustrative. Replace request, outcomes, identifiers and counts with observed session evidence; do not record these example results as facts. Inspect MCP isError, returned ok, and the recorded turn with gait_show when validating a new client/schema. Follow gait-session-tracking for branch checkout.

Frequently asked questions

What does the Catc Inventory AI skill do?

Catalyst Center device inventory and site management - list/filter devices by hostname, IP, platform, family, role, reachability; view site hierarchy; get interface details per device; device reachability monitoring; cross-reference with pyATS. Use when listing network devices, checking device reachability, auditing software versions, viewing site hierarchy, or finding a device by serial number. This is a narrow, purpose-built tool for that pyATS cross-reference workflow specifically. For anything else in Catalyst Center (wireless, assurance health, compliance, software images, events) or a...

Why use Catc Inventory on TypingMind?

Because you install it once and use it with any model. Catc Inventory 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 Catc Inventory in TypingMind?

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

Which AI models can use Catc Inventory?

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 Catc Inventory?

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

Is the Catc Inventory 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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