use-graphql-api
Über
Diese Fähigkeit ermöglicht die Kommandozeilen-Interaktion mit GraphQL-APIs unter Verwendung von Tools wie gh api graphql, curl und jq. Sie hilft Entwicklern, Schemas durch Introspektion zu erkunden, Abfragen/Mutationen zu konstruieren und Operationen durch die Verkettung von Daten zwischen Aufrufen zu verknüpfen. Nutzen Sie sie zur Automatisierung von GitHub-Workflows oder zur Integration beliebiger GraphQL-Endpunkte in CLI-Skripte.
Schnellinstallation
Claude Code
Empfohlennpx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/use-graphql-apiKopieren Sie diesen Befehl und fügen Sie ihn in Claude Code ein, um diese Fähigkeit zu installieren
Dokumentation
Use GraphQL API
Discover, construct, execute, and chain GraphQL operations from the command line.
When to Use
- Querying or mutating data via a GraphQL endpoint (GitHub, Hasura, Apollo, etc.)
- Automating GitHub operations that require GraphQL (Discussions, Projects v2)
- Building shell scripts that fetch structured data from GraphQL APIs
- Chaining multiple GraphQL calls where output of one feeds into the next
Inputs
- Required: GraphQL endpoint URL or service name (e.g.,
github) - Required: Operation intent (what data to read or write)
- Optional: Authentication token or method (default:
ghCLI auth for GitHub) - Optional: Output format preference (raw JSON, jq-filtered, variable assignment)
Procedure
Step 1. Discover the Schema
Determine available types, fields, queries, and mutations.
For GitHub:
# List available query fields
gh api graphql -f query='{ __schema { queryType { fields { name description } } } }' \
| jq '.data.__schema.queryType.fields[] | {name, description}'
# List available mutation fields
gh api graphql -f query='{ __schema { mutationType { fields { name description } } } }' \
| jq '.data.__schema.mutationType.fields[] | {name, description}'
# Inspect a specific type
gh api graphql -f query='{
__type(name: "Repository") {
fields { name type { name kind ofType { name } } }
}
}' | jq '.data.__type.fields[] | {name, type: .type.name // .type.ofType.name}'
For generic endpoints:
# Full introspection query via curl
curl -s -X POST https://api.example.com/graphql \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOKEN" \
-d '{"query":"{ __schema { types { name kind fields { name } } } }"}' \
| jq '.data.__schema.types[] | select(.kind == "OBJECT") | {name, fields: [.fields[].name]}'
Got: JSON output listing available types, fields, or mutations. The schema response confirms the endpoint is reachable and the auth token is valid.
If fail:
401 Unauthorized— verify the token; for GitHub, rungh auth statusCannot query field— the endpoint may disable introspection; consult its documentation instead- Connection refused — verify the endpoint URL and network access
Step 2. Identify the Operation Type
Determine whether your task requires a query (read), mutation (write), or subscription (stream).
| Intent | Operation | Example |
|---|---|---|
| Fetch data | query | Get repository details, list discussions |
| Create/update/delete | mutation | Create a discussion, add a comment |
| Real-time updates | subscription | Watch for new issues (rare in CLI) |
For GitHub-specific operations, consult the GitHub GraphQL API docs.
# Quick check: does the mutation exist?
gh api graphql -f query='{ __schema { mutationType { fields { name } } } }' \
| jq '.data.__schema.mutationType.fields[].name' | grep -i "discussion"
Got: Clear identification of whether a query or mutation is needed, plus the exact operation name (e.g., createDiscussion, repository).
If fail:
- Operation not found — search with broader terms or check the API version
- Unclear whether query or mutation — if the action changes state, it is a mutation
Step 3. Construct the Operation
Build the GraphQL query or mutation with fields, arguments, and variables.
Query example — fetch a repository's discussion categories:
gh api graphql -f query='
query($owner: String!, $repo: String!) {
repository(owner: $owner, name: $repo) {
discussionCategories(first: 10) {
nodes { id name }
}
}
}
' -f owner="OWNER" -f repo="REPO" | jq '.data.repository.discussionCategories.nodes'
Mutation example — create a GitHub Discussion:
gh api graphql -f query='
mutation($repoId: ID!, $categoryId: ID!, $title: String!, $body: String!) {
createDiscussion(input: {
repositoryId: $repoId,
categoryId: $categoryId,
title: $title,
body: $body
}) {
discussion { url number }
}
}
' -f repoId="$REPO_ID" -f categoryId="$CAT_ID" \
-f title="My Discussion" -f body="Discussion body here"
Key construction rules:
- Always use variables (
$var: Type!) instead of inline values for reusability - Request only the fields you need to minimize response size
- Use
first: Nwithnodesfor paginated connections - Add
idto every object selection — you will need it for chaining
Got: A syntactically valid GraphQL operation with appropriate variables, field selections, and pagination parameters.
If fail:
- Syntax errors — check bracket matching and trailing commas (GraphQL has no trailing commas)
- Type mismatch — verify variable types against the schema (e.g.,
ID!vsString!) - Missing required fields — add required input fields per the schema
Step 4. Execute via CLI
Run the operation and capture the response.
GitHub — using gh api graphql:
# Simple query
gh api graphql -f query='{ viewer { login } }'
# With variables
gh api graphql \
-f query='query($owner: String!, $repo: String!) {
repository(owner: $owner, name: $repo) { id name }
}' \
-f owner="octocat" -f repo="Hello-World"
# With jq post-processing
REPO_ID=$(gh api graphql \
-f query='query($owner: String!, $repo: String!) {
repository(owner: $owner, name: $repo) { id }
}' \
-f owner="OWNER" -f repo="REPO" \
--jq '.data.repository.id')
Generic endpoint — using curl:
curl -s -X POST "$GRAPHQL_ENDPOINT" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOKEN" \
-d "$(jq -n \
--arg query 'query { users { id name } }' \
'{query: $query}'
)"
Got: A JSON response with a data key containing the requested fields, or an errors array if the operation failed.
If fail:
errorsarray in response — read the message; common causes are missing permissions, invalid IDs, or rate limits- Empty
data— the query matched no records; verify input values - HTTP 403 — the token lacks the required scope; for GitHub, check
gh auth statusand add scopes withgh auth refresh -s scope
Step 5. Parse the Response
Extract the data you need from the JSON response.
# Extract a single value
gh api graphql -f query='{ viewer { login } }' --jq '.data.viewer.login'
# Extract from a list
gh api graphql -f query='
query($owner: String!, $repo: String!) {
repository(owner: $owner, name: $repo) {
issues(first: 5, states: OPEN) {
nodes { number title }
}
}
}
' -f owner="OWNER" -f repo="REPO" \
--jq '.data.repository.issues.nodes[] | "\(.number): \(.title)"'
# Assign to a variable for later use
CATEGORY_ID=$(gh api graphql -f query='
query($owner: String!, $repo: String!) {
repository(owner: $owner, name: $repo) {
discussionCategories(first: 20) {
nodes { id name }
}
}
}
' -f owner="OWNER" -f repo="REPO" \
--jq '.data.repository.discussionCategories.nodes[] | select(.name == "Show and Tell") | .id')
Got: Clean, extracted values ready for display or assignment to shell variables.
If fail:
jqreturns null — the field path is wrong; pipe raw JSON tojq .first to inspect structure- Multiple values when expecting one — add a
select()filter or| first - Unicode issues — add
-rto jq for raw string output
Step 6. Chain Operations
Use output from one operation as input to the next.
# Step A: Get the repository ID
REPO_ID=$(gh api graphql \
-f query='query($owner: String!, $repo: String!) {
repository(owner: $owner, name: $repo) { id }
}' \
-f owner="$OWNER" -f repo="$REPO" \
--jq '.data.repository.id')
# Step B: Get the discussion category ID
CAT_ID=$(gh api graphql \
-f query='query($owner: String!, $repo: String!) {
repository(owner: $owner, name: $repo) {
discussionCategories(first: 20) {
nodes { id name }
}
}
}' \
-f owner="$OWNER" -f repo="$REPO" \
--jq '.data.repository.discussionCategories.nodes[]
| select(.name == "Show and Tell") | .id')
# Step C: Create the discussion using both IDs
RESULT=$(gh api graphql \
-f query='mutation($repoId: ID!, $catId: ID!, $title: String!, $body: String!) {
createDiscussion(input: {
repositoryId: $repoId,
categoryId: $catId,
title: $title,
body: $body
}) {
discussion { url number }
}
}' \
-f repoId="$REPO_ID" -f catId="$CAT_ID" \
-f title="$TITLE" -f body="$BODY" \
--jq '.data.createDiscussion.discussion')
echo "Created: $(echo "$RESULT" | jq -r '.url')"
Pattern: Always extract id fields in earlier queries so they can be passed as ID! variables to subsequent mutations.
Got: A multi-step workflow where each call succeeds and IDs flow correctly between operations.
If fail:
- Variable is empty — a previous step failed silently; add
set -eand check each intermediate value - ID format wrong — GitHub node IDs are opaque strings (e.g.,
R_kgDO...); never construct them manually - Rate limited — add
sleep 1between calls or batch queries using aliases
Validation
- Introspection query returns schema data (Step 1 succeeds)
- Constructed queries are syntactically valid (no GraphQL parser errors)
- Responses contain
datakeys withouterrors - Extracted values match expected types (IDs are non-empty strings, counts are numbers)
- Chained operations complete end-to-end (mutation uses IDs from prior queries)
Pitfalls
| Pitfall | Prevention |
|---|---|
Forgetting ! on required variable types | Always check schema for nullability; most input fields are non-null (!) |
| Using REST IDs in GraphQL | GraphQL uses opaque node IDs; fetch them via GraphQL, not REST |
| Not paginating large result sets | Use first/after with pageInfo { hasNextPage endCursor } |
| Hardcoding IDs instead of querying them | IDs differ between environments; always query dynamically |
Ignoring the errors array | Check for errors even when data is present — partial errors are possible |
| Shell quoting issues with nested JSON | Use --jq flag with gh or pipe through jq separately |
Related Skills
- scaffold-nextjs-app — scaffolding web apps that consume GraphQL APIs
- create-pull-request — GitHub workflow automation (REST-based counterpart)
- manage-git-branches — Git operations often paired with API automation
- serialize-data-formats — JSON parsing patterns used in response handling
GitHub Repository
Verwandte Skills
content-collections
MetaDiese Skill bietet eine produktionsgetestete Einrichtung für Content Collections – ein TypeScript-first-Tool, das Markdown/MDX-Dateien in typsichere Datensammlungen mit Zod-Validierung umwandelt. Verwenden Sie ihn beim Erstellen von Blogs, Dokumentationsseiten oder inhaltsstarken Vite + React-Anwendungen, um Typsicherheit und automatische Inhaltsvalidierung zu gewährleisten. Er behandelt alles von der Vite-Plugin-Konfiguration und MDX-Kompilierung bis hin zur Deployment-Optimierung und Schema-Validierung.
polymarket
MetaDiese Fähigkeit ermöglicht es Entwicklern, Anwendungen mit der Polymarket-Prognosemärkte-Plattform zu erstellen, einschließlich API-Integration für Handel und Marktdaten. Sie bietet außerdem Echtzeit-Datenstreaming über WebSocket, um Live-Trades und Marktaktivitäten zu überwachen. Nutzen Sie sie zur Implementierung von Handelsstrategien oder zur Erstellung von Tools, die Live-Marktaktualisierungen verarbeiten.
creating-opencode-plugins
MetaDiese Fähigkeit unterstützt Entwickler dabei, OpenCode-Plugins zu erstellen, die in über 25 Ereignistypen wie Befehle, Dateien und LSP-Operationen eingreifen. Sie bietet die Plugin-Struktur, Event-API-Spezifikationen und Implementierungsmuster für JavaScript/TypeScript-Module. Nutzen Sie sie, wenn Sie den Lebenszyklus des OpenCode KI-Assistenten mit benutzerdefinierter ereignisgesteuerter Logik abfangen, überwachen oder erweitern müssen.
sglang
MetaSGLang ist ein hochperformantes LLM-Serving-Framework, das sich auf schnelle, strukturierte Generierung für JSON, Regex und agentenbasierte Workflows unter Verwendung seines RadixAttention-Prefix-Cachings spezialisiert. Es bietet deutlich schnellere Inferenz, insbesondere für Aufgaben mit wiederholten Präfixen, was es ideal für komplexe, strukturierte Ausgaben und Mehrfachdialoge macht. Wählen Sie SGLang gegenüber Alternativen wie vLLM, wenn Sie constrained decoding benötigen oder Anwendungen mit umfangreicher Präfix-Weitergabe entwickeln.
