cel-programs

A skill for building CEL data streams that collect information from APIs. CEL is a language used to describe API requests and data-processing logic, while mito is a command-line tool for testing it.

In plain words
What is it for?
Writing CEL programs, configuring cel.yml.hbs templates and manifests, handling authentication and pagination, and testing with mito.
Why use it?
It imposes a mock-first workflow that catches collection and pagination problems before templates and integration tests are written.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/elastic/integration-skills/cel-programs
Any agent
npx skills add elastic/integration-skills --skill cel-programs
Clone the repo
git clone --depth 1 https://github.com/elastic/integration-skills

Made for: Claude Code, Codex.

Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,278 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00065 $0.05278
Opus 5 $0.00032 $0.02639
Sonnet 5 $0.00013 $0.01056
Haiku 4.5 $0.00006 $0.00528

Measured yesterday against content hash 2f980d088645, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cel-programs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/cel-programs/SKILL.md · 326 lines

How it starts

The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.

cel-programs

When to use

Use this skill when tasks include:

  • creating or editing cel.yml.hbs agent stream templates
  • configuring data stream manifests for the cel input type
  • writing CEL programs with pagination, cursor management, or authentication
  • testing or debugging a CEL program locally with mito
  • setting up system tests with mock APIs for CEL-based data streams
  • prototyping a new CEL-based data stream's collection logic
  • any CEL or mito question, regardless of context

When not to use

Do not use this skill as the primary guide for:

  • ingest pipeline processor design (ingest-pipelines)
  • ECS field mapping (ecs-field-mappings)
  • package scaffolding (create-integration)
  • system test execution with the Elastic stack (integration-testingreferences/system-testing.md)

Mandatory workflow — mock → mito → template

This is not a suggestion. Every CEL program MUST be developed in this order. The subagent must not write cel.yml.hbs until the CEL program has been validated with mito against a running mock. Skipping steps or reordering causes failures that are hard to debug.

Do NOT write more than ~10–15 new lines of CEL before running mito. Build the program incrementally in phases (skeleton → error handling → event mapping → pagination → cursor guard), validating with mito after each phase. Writing a large program in one shot leads to cascading compilation errors that are extremely hard to debug. Follow the phased approach in references/cel-incremental-build.md.

Step Action Output
1. Create the system test mock Write the elastic/stream config at _dev/deploy/docker/files/config-<stream>.yml with rules matching all API endpoints. Write test-default-config.yml. Mock config file, docker-compose service, test config
2. Start the mock locally stream http-server --addr=:8090 --config=... Running mock at http://localhost:8090
3. Create a plain .cel file and state.json Write the CEL program as a standalone .cel file. Create state.json with the same keys the future state: block will contain, but with literal test values instead of Handlebars. Point url at the local mock. program.cel, state.json in /tmp or working dir
4. Run mito and iterate Build incrementally per references/cel-incremental-build.md: Phase 0 skeleton → Phase 1 error handling → Phase 2 events → Phase 3 pagination → Phase 4 cursor. Run mito -data state.json -log_requests program.cel after each phase. Do not proceed until mito output is correct. Validated CEL program
5. ONLY THEN write cel.yml.hbs Copy the working CEL expression into program: | in the Handlebars template. Replace literal test values with {{var}} references. Configure manifests. Final integration template

Read the full file on GitHub · 326 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 326 lines · 65 tokens per session scan A 2f980d088645

Subscribe to this mod's changes

cel-programs is a skill published in the GitHub repository elastic/integration-skills (15 stars, last pushed 4d ago), licensed Apache-2.0. It adds 65 tokens to every session and 5,278 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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