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Agent skill

Create Rule

by cartography-cncf in cartography-cncf/cartography

Author a Cartography security rule (one or more Cypher Facts plus a Pydantic Finding output model) under cartography/rules/data/rules/.

Apache-2.0Auto-check passedSecurity

Install Create Rule

skills CLI
$ npx skills add cartography-cncf/cartography --skill create-rule -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install cartography-cncf/cartography create-rule --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/cartography-cncf/cartography.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/create-rule .claude/skills/create-rule && rm -rf skills-src

Use ~/.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/

Facts

Skill name
create-rule
GitHub stars
4.1k
Token cost
~3k tokens
SKILL.md length
825 words
Files
4 (incl. references)
Skills in repo
11
Repo updated
First seen
Licence
Apache-2.0

At a glance

Author a Cartography security rule (one or more Cypher Facts plus a Pydantic Finding output model) under cartography/rules/data/rules/.

  • Works in 7 steps: Imports → Author Facts → Define the Finding output model → …
  • The user asks to add a security check
  • SKILL.md covers Architecture, Critical rules, Instructions and Compliance frameworks, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Create Rule is an agent skill from cartography-cncf/cartography. Author a Cartography security rule (one or more Cypher Facts plus a Pydantic Finding output model) under cartography/rules/data/rules/. Use when the user asks to add a security check, detection, attack-surface query, compliance control, CIS benchmark rule, or cross-cloud detection.

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/cis-conventions.md`, `references/compliance-frameworks.md` and `references/ontology-in-rules.md`).

It sits in Security, covering Threat modeling. It works with Pydantic. The repository describes itself as: Cartography is a Python tool that pulls infrastructure assets and their relationships into a Neo4j graph database. The licence is Apache-2.0.

When your agent uses it

  • The user asks to add a security check
  • Attack-surface query
  • Compliance control
  • CIS benchmark rule

Example prompts

  • “/create-rule”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Imports
  2. Author Facts
  3. Define the Finding output model
  4. Compose the Rule
  5. Maturity, versioning, tagging
  6. Register the Rule
  7. Test it

What it can do on your machine

Read from SKILL.md and the folder at commit e345364. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Create Rule loads about 3k tokens when it runs, and up to ~6.4k if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 825 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.4k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from cartography-cncf/cartography at commit e345364, republished under its Apache-2.0 licence (© cartography-cncf). 825 words, ~3,044 tokens.

Download SKILL.mdSave it as .claude/skills/create-rule/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
create-rule
description
Author a Cartography security rule (one or more Cypher Facts plus a Pydantic Finding output model) under `cartography/rules/data/rules/`. Use when the user asks to add a security check, detection, attack-surface query, compliance control, CIS benchmark rule, or cross-cloud detection.

create-rule

Cartography rules detect attack surfaces, security gaps, and compliance issues across the graph. Rules are composed of one or more Facts (Cypher queries) and a Finding output model (Pydantic).

Architecture

Rule (e.g., "database-exposed")
  ├─ Fact (e.g., "aws-rds-public")
  ├─ Fact (e.g., "azure-sql-public")
  └─ Fact (e.g., "gcp-cloudsql-public")
  • Rule — represents a security issue / attack surface.
  • Fact — single Cypher query that gathers evidence.
  • Finding — Pydantic model defining the result row structure.

Critical rules

  1. cypher_query aliases must match Finding field names exactly. Use RETURN x.id AS id, x.name AS name.
  2. cypher_visual_query returns nodes, not properties — used for graph viz.
  3. All Finding fields are | None with default None. The source field is auto-populated.
  4. source and extra are reserved. Never alias them in a cypher_query; use ontology_source for _ont_source.
  5. The cypher_query must match the declared asset_label. MATCH (k:APIKey) WHERE k:OpenAIApiKey ..., not MATCH (k) WHERE k:OpenAIApiKey ..., so the rows returned cannot diverge from the asset claimed.
  6. Compliance metadata uses frameworks=, not tags. Keep tags for categories only (iam, credentials, stride:*).
  7. Rule IDs and names describe the Cartography security detection, not the compliance control. Put framework scope, requirement/control id, and external control title in frameworks=.

Instructions

Step 1 — Imports
python
from cartography.rules.spec.model import (
    Fact,
    Finding,
    Framework,
    Maturity,
    Module,
    Rule,
    RuleReference,
)
Step 2 — Author Facts

A Fact is a Cypher query that detects one specific condition:

python
_aws_public_databases = Fact(
    id="aws-rds-public",
    name="Publicly accessible AWS RDS instances",
    description="AWS RDS databases exposed to the internet",
    cypher_query="""
    MATCH (db:AWSRDSInstance)
    WHERE db.publicly_accessible = true
    RETURN db.id AS id, db.db_instance_identifier AS name, db.region AS region
    """,
    cypher_visual_query="""
    MATCH (db:AWSRDSInstance)
    WHERE db.publicly_accessible = true
    RETURN db
    """,
    cypher_count_query="""
    MATCH (db:AWSRDSInstance)
    RETURN COUNT(db) AS count
    """,
    identity_fields=("id",),
    module=Module.AWS,
    maturity=Maturity.STABLE,
)

Fact fields:

FieldRequiredNotes
idYeslowercase + hyphens
nameYeshuman-readable
descriptionYeswhat this fact detects
cypher_queryYesstructured rows; AS aliases match Finding fields
cypher_visual_queryYesreturns nodes for visualization
cypher_count_queryYestotal assets evaluated; RETURN COUNT(...) AS count
moduleYesModule.AWS, Module.AZURE, Module.GCP, ...
maturityYesMaturity.EXPERIMENTAL or Maturity.STABLE
asset_id_fieldNofinding field that uniquely identifies an asset (dedupe)
identity_fieldsYestuple of output-model fields forming the finding's stable logical identity across syncs (for downstream lifecycle tracking); required with no default, distinct from asset_id_field
Step 3 — Define the Finding output model
python
class DatabaseExposedOutput(Finding):
    """Output model for publicly exposed databases."""
    name: str | None = None    # human-readable label first: used as the finding title
    id: str | None = None
    region: str | None = None
  • Inherit from Finding.
  • Field names must match cypher_query aliases exactly.
  • All fields are | None with default None.
  • The source field is auto-populated with the module name and is reserved: do not return a source column. Alias the per-row ontology provider ontology_source and declare it on the model.
  • Declare a human-readable label as the first field. Downstream consumers derive the finding's title from the first non-empty field in declaration order, so leading with an opaque id, ARN, URI, digest, region, or boolean produces an unreadable title. If the node has no natural name, alias one in the cypher_query (e.g. coalesce(n.friendly_name, n.short_id) AS name, or an AWS Name tag) and declare it first. This is independent of identity_fields/asset_id_field and of RETURN order. See "Display field order (finding title)" in docs/root/usage/rules.md.
  • Set identity_fields on the Fact (required) to the subset of these fields that forms the finding's stable logical identity, excluding volatile context (*_count, days_*, last_used*, *_date, posture booleans, aggregate lists) so downstream lifecycle tracking does not treat a changed metric as a new finding. See "Finding identity vs. display fields" in docs/root/usage/rules.md.
Show full SKILL.md (353 more words)Show less
Step 4 — Compose the Rule
python
database_exposed = Rule(
    id="database-exposed",
    name="Publicly Accessible Databases",
    description="Detects databases exposed to the internet across cloud providers",
    output_model=DatabaseExposedOutput,
    tags=("infrastructure", "attack_surface", "database"),
    facts=(_aws_public_databases, _azure_public_databases, _gcp_cloudsql_public),
    version="1.0.0",
)

Rule fields:

FieldRequiredNotes
idYeslowercase + underscores
nameYeshuman-readable
descriptionYeswhat security issue this detects
output_modelYesPydantic model class
tagsYestuple of categorisation tags (no compliance)
factsYestuple of Fact objects
versionYessemantic version string
referencesNolist of RuleReference for documentation
frameworksNotuple of Framework (compliance metadata)
Step 5 — Maturity, versioning, tagging
  • Maturity.EXPERIMENTAL — new, may have bugs / perf issues. Use for testing detection capabilities.
  • Maturity.STABLE — production-ready, well-tested, optimized.

Versioning follows semver (0.1.0 initial, 0.2.0 add facts, 0.2.1 bug fix, 1.0.0 production-ready).

Tag categories:

  • Category: infrastructure, identity, data, network, compute.
  • Type: attack_surface, misconfiguration, compliance, vulnerability.
  • Provider: aws, azure, gcp, github, okta.
  • Threat model: stride:spoofing, stride:tampering, stride:repudiation, stride:information_disclosure, stride:denial_of_service, stride:elevation_of_privilege.
Step 6 — Register the Rule

In cartography/rules/data/rules/__init__.py:

python
from cartography.rules.data.rules.my_security_rule import my_security_rule

RULES = {
    # ... existing rules
    my_security_rule.id: my_security_rule,
}
Step 7 — Test it
bash
cartography-rules list my_security_rule
cartography-rules run my_security_rule
cartography-rules run my_security_rule --output json
cartography-rules run my_security_rule --no-experimental

Compliance frameworks

For CIS, NIST, SOC2, etc., attach a Framework object or framework helper instead of polluting tags:

python
from cartography.rules.data.frameworks.cis import cis_aws

my_rule = Rule(
    id="aws_access_keys_not_rotated",
    name="Access Keys Not Rotated",
    # ...
    tags=("iam", "credentials", "stride:spoofing"),  # category tags only
    frameworks=(
        cis_aws("1.14"),
    ),
)

Compliance-style tags like cis:1.14, cis:aws-5.0 must NOT live in tags. CLI users filter via --framework CIS, --framework CIS:aws, --framework CIS:aws:5.0.

For framework helpers with known canonical controls, the helper fills Framework.control_title. For custom mappings, set Framework(control_title="...") to the external framework control or requirement title. Keep Rule.name as reusable Cartography security copy. Many Cartography rules may map to the same framework control.

Framework helpers encode the one active revision Cartography supports for each benchmark scope today. If Cartography needs to report against multiple benchmark revisions later, add version-aware helpers or explicit framework objects instead of mixing revisions in one helper.

For deeper framework guidance, including CIS benchmark conventions (rule names, IDs, file naming, headers, references), see references/compliance-frameworks.md and references/cis-conventions.md.

Cross-provider rules

Group facts from different cloud providers under one rule. Each fact's cypher_query should include the provider in the result so the Finding has it:

python
_aws_unencrypted_storage = Fact(
    id="aws-s3-unencrypted",
    cypher_query="""
    MATCH (b:AWSS3Bucket) WHERE b.default_encryption IS NULL
    RETURN b.id AS id, b.name AS name, 'aws' AS provider
    """,
    # ...
    module=Module.AWS,
    maturity=Maturity.STABLE,
)


_azure_unencrypted_storage = Fact(
    id="azure-storage-unencrypted",
    cypher_query="""
    MATCH (s:AzureStorageAccount) WHERE s.encryption_enabled = false
    RETURN s.id AS id, s.name AS name, 'azure' AS provider
    """,
    module=Module.AZURE,
    maturity=Maturity.STABLE,
)


class UnencryptedStorageOutput(Finding):
    id: str | None = None
    name: str | None = None
    provider: str | None = None


unencrypted_storage = Rule(
    id="unencrypted_storage",
    name="Unencrypted Cloud Storage",
    description="Detects unencrypted storage across cloud providers",
    output_model=UnencryptedStorageOutput,
    tags=("data", "encryption", "compliance"),
    facts=(_aws_unencrypted_storage, _azure_unencrypted_storage),
    version="1.0.0",
)

Using the ontology

Leverage semantic labels (e.g. UserAccount) and _ont_* properties for cross-module detection:

python
_unmanaged_accounts = Fact(
    id="unmanaged-accounts-ontology",
    name="User Accounts Not Linked to Identity",
    description="Detects user accounts without a corresponding User identity",
    cypher_query="""
    MATCH (ua:UserAccount)
    WHERE NOT (ua)<-[:HAS_ACCOUNT]-(:User)
    RETURN ua.id AS id, ua._ont_email AS email, ua._ont_source AS ontology_source
    """,
    cypher_visual_query="""
    MATCH (ua:UserAccount)
    WHERE NOT (ua)<-[:HAS_ACCOUNT]-(:User)
    RETURN ua
    """,
    cypher_count_query="""
    MATCH (ua:UserAccount)
    RETURN COUNT(ua) AS count
    """,
    asset_label="UserAccount",
    asset_id_field="id",
    identity_fields=("ontology_source", "id"),
    module=Module.CROSS_CLOUD,
    maturity=Maturity.STABLE,
)

For semantic-label setup, see the enrich-ontology skill.

References (load on demand)

  • references/compliance-frameworks.md — Framework field reference, CLI filtering, Rule.has_framework() checks.
  • references/ontology-in-rules.md — using UserAccount / Tenant / Database labels and _ont_* props in rule queries.
  • references/cis-conventions.md — CIS rule naming, IDs, file layout, headers, references, complete CIS example.

© cartography-cncf, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in .agents/skills/create-rule of cartography-cncf/cartography.

  • SKILL.md
  • references/cis-conventions.md
  • references/compliance-frameworks.md
  • references/ontology-in-rules.md

Open the folder on GitHubat commit e345364

Compare with similar skills

Create Rule 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.

Create Rule compared with similar skills
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Forensifyalexgreensh/repo-forensics188—~2.5kAutomated safety check: NotesCustom licence
Commit Security Scancodexstar69/bug-hunter519—~629Automated safety check: PassMIT
Auditing Code For Vulnerabilitiestrilwu/secskills157—~3.2kAutomated safety check: PassMIT
Threat Mitigation Mappingwshobson/agents40k8 repos~742Automated safety check: PassMIT

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  • Enrich Ontology

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Works with

Categories

Questions about Create Rule

What does Create Rule do?

Author a Cartography security rule (one or more Cypher Facts plus a Pydantic Finding output model) under cartography/rules/data/rules/. Create Rule is an agent skill from cartography-cncf/cartography. Author a Cartography security rule (one or more Cypher Facts plus a Pydantic Finding output model) under cartography/rules/data/rules/.

When should I use Create Rule?

Create Rule fits situations like: the user asks to add a security check; attack-surface query; compliance control; CIS benchmark rule.

How do I install Create Rule in Claude Code?

Run `npx skills add cartography-cncf/cartography --skill create-rule -a claude-code`. Or copy the skill folder (.agents/skills/create-rule in cartography-cncf/cartography) into .claude/skills/create-rule in your project. Claude Code loads it when a task matches its description.

How do I install Create Rule in Codex?

Run `npx skills add cartography-cncf/cartography --skill create-rule -a codex`. Or copy the skill folder (.agents/skills/create-rule in cartography-cncf/cartography) into .agents/skills/create-rule in your project. Codex loads it when a task matches its description.

Can I use Create Rule in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add cartography-cncf/cartography --skill create-rule -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/create-rule, .gemini/skills/create-rule, .github/skills/create-rule and .opencode/skills/create-rule in your project.

What does Create Rule need to run?

SKILL.md names no scripts, command-line tools or credentials: Create Rule is instructions for the agent only. Our summary lists: Python 3.

Does Create Rule access the network?

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.

Is Create Rule safe to install?

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.

What licence does Create Rule use?

Create Rule is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Create Rule use?

About 3k tokens (SKILL.md is roughly 12k 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 3.3k tokens, read only when the agent opens those files.

What are the alternatives to Create Rule?

Skills that share tags, products or a category with Create Rule: Fla Ascend Performance (fla-org/flash-linear-attention, 5.8k stars), Forensify (alexgreensh/repo-forensics, 188 stars), Commit Security Scan (codexstar69/bug-hunter, 519 stars) and Auditing Code For Vulnerabilities (trilwu/secskills, 157 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Create Rule?

cartography-cncf (a GitHub organization) maintains it in cartography-cncf/cartography, which has 4,128 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 9, 2026.

Source: cartography-cncf/cartography on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.