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.
npx agentmods add skills/coralogix/cx-cli/add-commandnpx skills add coralogix/cx-cli --skill add-commandgit clone --depth 1 https://github.com/coralogix/cx-cliWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00126 | $0.02376 |
| Opus 5 | $0.00063 | $0.01188 |
| Sonnet 5 | $0.00025 | $0.00475 |
| Haiku 4.5 | $0.00013 | $0.00238 |
Grade A, and why
add-command 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 2d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add a CLI Command
End-to-end workflow for adding a new command to cx. Every command falls into one of two archetypes - determine which one first, then follow the corresponding steps.
docs/adding-a-command.md has copy-pasteable code templates for every step below. Read it alongside this workflow.
Step 0: Understand What You're Building
Before writing any code, get clarity on the domain:
- What Coralogix API are you wrapping? Find the API docs or example responses. Understand the data model - what entities exist, what fields they have, what operations are supported.
- What should the user be able to do? List the subcommands (e.g.,
list,get,create) and what flags make sense. - Does this belong under a wrapper group? The CLI organizes related commands into wrapper groups. Check if your command fits under an existing group before creating a top-level command:
cx alerts- alert definitions +schedulerscx notifications-connectors,routers,presets,testcx webhooks- outgoing webhooks +actionscx enrichments- enrichment rules +customenrichment tablescx integrations- integrations +extensions,contextual-datacx iam-api-keys,roles,scopes,users,groups,ip-accessRuncx schemato see the full command tree as JSON.
- Which archetype fits?
| Archetype | When to use | Reference implementation |
|---|---|---|
| A: DataPrime-based | Querying logs, spans, or any DataPrime source | src/commands/logs/mod.rs |
| B: REST-based | Wrapping a Coralogix REST API (most new commands) | src/commands/alerts/api.rs + src/commands/alerts/mod.rs |
DataPrime commands delegate to a shared pipeline and require minimal code (~130 lines). REST commands build the full pipeline (API client, fan-out, merge, render) - more code but more control.
Important: All API integrations must use REST (HTTP). The CLI is HTTP-only by design - do not use gRPC.
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.
- 2d ago First seen · 147 lines · 126 tokens per session scan A 03522f37b652
add-command is a skill published in the GitHub repository coralogix/cx-cli (115 stars, last pushed 2d ago), licensed Apache-2.0. It adds 126 tokens to every session and 2,376 once invoked, about $0.0006 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 2026-08-30.
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brainstorming
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auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…