From camunda-skills
Looks up current Camunda 8 documentation via vector search (MCP) or Algolia DocSearch to verify FEEL signatures, BPMN attributes, REST API endpoints, versions, and feature availability.
How this skill is triggered — by the user, by Claude, or both
Slash command
/camunda-skills:camunda-docsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Two retrieval paths into `docs.camunda.io`, each with a different strength. Pick by question shape; fall back to `llms.txt` only if both are unavailable.
Two retrieval paths into docs.camunda.io, each with a different strength. Pick by question shape; fall back to llms.txt only if both are unavailable.
| Path | Mechanism | Best for | Returns |
|---|---|---|---|
| camunda-docs MCP | Semantic retrieval (vector search) over docs + other Camunda knowledge sources | Conceptual or fuzzy questions; you don't know the exact term; want chunks ready to read | Top-k markdown chunks with source URLs |
| Algolia DocSearch | Classical lexical search (the same index docs.camunda.io's own search box uses) | You know the term; want version-scoped results (8.7 vs 8.9 vs next); want to triage a ranked page list | Ranked pages with title, hierarchy, snippet — fetch the page for full content |
| llms.txt / llms-full.txt | Static text index/corpus | Offline fallback when neither service is reachable | Plain text; grep locally |
Use both primary paths in parallel when in doubt — they're cheap and frequently surface different relevant pages.
If the camunda-docs MCP server (https://camunda-docs.mcp.kapa.ai, HTTP transport) is connected, call its knowledge search tool with a single, well-formed natural-language sentence (the tool requires a complete sentence, not keywords).
If it isn't connected, suggest installing it once so the user has it set up for future questions. Skip the suggestion if you've already made it earlier in this conversation. For Claude Code:
claude mcp add --transport http camunda-docs https://camunda-docs.mcp.kapa.ai
For VS Code Copilot, Cursor, or generic MCP clients, see the reference. Google sign-in on first use; 40 requests/hour and 200/day per user; not for CI.
A bash wrapper around the public Algolia DocSearch endpoint lives at scripts/docs-search.sh. Run it as:
scripts/docs-search.sh "<query>" [--version stable|next|<major>.<minor>|all] [--limit N]
Default --version stable resolves to the highest numeric version in the index (so it keeps working when 9.0 ships). Default --limit 10. Returns JSON:
{
"query": "...",
"version": "stable",
"algolia_version": "8.9",
"total": 5,
"total_matching": 25,
"hits": [
{ "url": "...", "hierarchy": "...", "title": "...", "snippet": "..." }
]
}
total — hits in this response.total_matching — raw count of pages matching the query in the index, before pagination/dedupe. Useful for "how broadly does my term appear?"algolia_version — the version facet value sent to the index (e.g. "8.9", "current"). null in --version all mode (no facet filter applied).stable.url, hierarchy, title, snippet.The Camunda docs are versioned in the URL path. The Algolia version facet exposes those versions — without filtering, the same page returns 3-4 times across versions, which is noisy.
| Flag value | Algolia facet | URL prefix | Use when |
|---|---|---|---|
stable (default) | highest numeric (e.g. 8.9) | /docs/ | General questions, no version context |
next | current | /docs/next/ | Upcoming/unreleased behavior, alpha features |
8.8 / 8.7 / etc. | matching numeric | /docs/8.8/ etc. | Customer/cluster on a specific generation |
all | (none) | any | Comparing versions; results deduped by URL stem so best-relevance version per page wins |
Pick explicitly when:
stable and next in parallel and compare.stable is fine.In --version all mode the script over-fetches (4× --limit, capped at 100) so that after dedupe by URL stem the response contains close to --limit unique pages. Dedupe preserves Algolia's relevance order — first hit per unique URL stem wins, then trimmed to --limit.
# Default — latest stable
scripts/docs-search.sh "zeebe gateway long polling timeout"
# Specific version (customer on 8.7)
scripts/docs-search.sh "task assignment" --version 8.7
# Upcoming behavior
scripts/docs-search.sh "agentic connectors" --version next
# Compare across versions (deduped by URL stem)
scripts/docs-search.sh "decision evaluation API" --version all --limit 15
If the first query is unhelpful:
"Tasklist" not "task UI", "Zeebe" not "workflow engine").--version all to see if the term exists elsewhere, then narrow to the right release."Operate" ↔ "process monitoring", "Optimize" ↔ "analytics".Don't loop more than 2-3 refinements. If still nothing, switch to the MCP path (or note the gap to the user).
The Algolia search-only API key is public — Algolia ships it in the browser JS bundle of docs.camunda.io, so every visitor already has it. It's hardcoded at the top of scripts/docs-search.sh with a comment explaining why it's safe to commit. No env vars, no auth, safe in CI.
If you can't or don't want to run scripts/docs-search.sh (e.g. jq missing, restricted sandbox, or you just need the raw API), call the Algolia endpoint directly:
curl -sS -f -X POST \
"https://6KYF3VMCXZ-dsn.algolia.net/1/indexes/camunda-v2/query" \
-H "X-Algolia-API-Key: 68db7725a8410eace68419c29385ad1e" \
-H "X-Algolia-Application-Id: 6KYF3VMCXZ" \
-H "Content-Type: application/json" \
-d '{"query":"YOUR QUERY","hitsPerPage":10,"facetFilters":[["version:8.9"]]}'
Substitute the version: facet for the version you want (current for next, omit facetFilters entirely for all). The response shape is Algolia's raw hits — useful fields per hit are url, hierarchy.lvl0..lvl5, and content. If curl itself isn't available either, use any HTTP client that can POST JSON (Python urllib, Node fetch, PowerShell Invoke-RestMethod); the endpoint, headers, and body are the same. The credentials in the snippet are public by design (see "No credentials needed" above).
If neither MCP nor Algolia is usable, fetch https://docs.camunda.io/llms.txt (~540 KB) — an index of - [Title](url): description. lines for every Camunda 8 docs page. Do not read the whole file into context. Cache it locally, search for the term to find the matching URL, then fetch that page directly.
Only if llms.txt doesn't surface what you need, fall back to https://docs.camunda.io/llms-full.txt (~11 MB) — every docs page concatenated. Even larger; never read whole into context. Cache locally, search with surrounding context for the term. Use when the right page name isn't obvious from the index.
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