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coralogix-ai-center

coralogix-ai-center is a skill for Claude Code, Codex from aws/tools-for-devops-agent. It costs 123 tokens per session (15,613 once invoked), scanned A, original, Apache-2.0.

A guide for observing and evaluating generative-AI applications and agents in Coralogix. It covers model interactions, response quality, hallucinations, tokens, cost, latency, security risks, and guardrail results.

In plain words
What is it for?
Use it to analyse AI prompts and responses, evaluate answer quality, track token use and cost, investigate latency and errors, and review guardrails or AI security risks.
Why use it?
It helps teams see what AI applications are doing instead of treating their prompts and responses as a black box. It supports finding quality, cost, performance, and security problems.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; mentions Codex; mentions Gemini CLI.

not rated 137repo +17 today A scan 123 tokens original Apache-2.0

Good fit Use it to analyse AI prompts and responses, evaluate answer quality, track token use and cost, investigate latency and errors, and review guardrails or AI security risks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aws/tools-for-devops-agent/coralogix-ai-center
View source ↗ aws/tools-for-devops-agent aws.github.io
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.

Any agent
npx skills add aws/tools-for-devops-agent --skill coralogix-ai-center
Clone the repo
git clone --depth 1 https://github.com/aws/tools-for-devops-agent

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for coralogix-ai-center

README.md
[![agentmods](https://agentmods.dev/badge/skills/aws/tools-for-devops-agent/coralogix-ai-center/github.svg)](https://agentmods.dev/skills/aws/tools-for-devops-agent/coralogix-ai-center)
Your own site
<a href="https://agentmods.dev/skills/aws/tools-for-devops-agent/coralogix-ai-center"><img src="https://agentmods.dev/badge/skills/aws/tools-for-devops-agent/coralogix-ai-center/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for coralogix-ai-center

Your own site · 80×15
<a href="https://agentmods.dev/skills/aws/tools-for-devops-agent/coralogix-ai-center"><img src="https://agentmods.dev/badge/skills/aws/tools-for-devops-agent/coralogix-ai-center.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 123 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 15,613 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00123 $0.15613
Opus 5.5 $0.00049 $0.06245
Sonnet 5.5 $0.00025 $0.03123
Haiku 4.5 $0.00012 $0.01561

Measured yesterday against content hash f95a0d6d347a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

coralogix-ai-center 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/coralogix-ai-center/SKILL.md · 468 lines

How it starts

The opening of the file, as written. The whole thing — 468 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Center — analyzing GenAI interactions, quality & platform health

Background

AI Center is Coralogix's native generative-AI observability and security platform. It captures every LLM interaction as OpenTelemetry GenAI spans and gives full-stack visibility into AI applications — what users ask, how well the AI answers, where it hallucinates, token usage and cost, latency, errors, security risks, and guardrail/evaluation outcomes. It exists because GenAI apps are black boxes by default: teams can't see hallucinations, cost overruns, prompt-injection/PII risks, or quality regressions. AI Center closes that gap.

Capabilities you support (a question may span several of these):

  • Monitoring / Observability — interactions, cost, tokens, latency, errors, usage per app/model/user.
  • Evaluations — automatically score interaction quality/security/compliance against policies (results land on spans as tags).
  • Guardrails — real-time blocking of harmful/non-compliant prompts or responses via the cx-guardrails SDK.
  • AI‑SPM (AI Security Posture Management) — discover AI usage across code (GitHub scan), security posture score, risky users.

Two data sources:

  • Telemetry — GenAI spans, queried with query_dataprime (source spans). Use for content, cost, tokens, latency, errors, usage, and issues over time. See the coralogix-spans (skill://coralogix-spans/SKILL.md) and coralogix-dataprime (skill://coralogix-dataprime/SKILL.md) skills for span querying and DataPrime syntax.
  • Configuration — the ai_center_* (read) and manage_ai_* (write) tools. Use for the AI app inventory, configured evaluations/policies, custom evaluations, and model pricing — none of which live in spans.

Objectives

  • Answer from real telemetry: for content/quality questions read the actual interactions (report coverage — see Golden rule); for everything else compute from tags/aggregations.
  • Compose your own minimal scoped query for exactly what's asked. The widget reference below teaches how each widget query is built — use it as your inspiration: when a question maps to a widget logic, adapt that widget's DataPrime query; when it doesn't, build your own query, and be helped and inspired with the logic of the closest/related widgets to compose the query. Always apply the GenAI filter and inject the user's params (timeframe, app, model, user).
  • Back findings with evidence — quoted messages, traceIDs, concrete counts, etc. (a trend is an insight you draw, not evidence) — and suggest next steps. Cite the traceID of any interaction you reference.

Read the full file on GitHub · 468 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 468 lines · 123 tokens per session scan A f95a0d6d347a

Subscribe to this mod's changes

coralogix-ai-center is a skill published in the GitHub repository aws/tools-for-devops-agent (137 stars, last pushed today), licensed Apache-2.0. It adds 123 tokens to every session and 15,613 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-11-05.

Data and AIDevOps and cloudSecurityagent-skillsagentsaiopsawsaws-devops-agent
Related

coralogix-ai-center compared with skills from other repositories

coralogix-ai-center next to 6 skills from other repositories
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coralogix-ai-centeraws/tools-for-devops-agentSkill137todayApache-2.0A123Claude Code, Codex
dataset-transformationawslabs/agent-pluginsSkill937yesterdayApache-2.0A110Claude Code
dataset-evaluationawslabs/agent-pluginsSkill937yesterdayApache-2.0A93Claude Code
use-case-specificationawslabs/agent-pluginsSkill937yesterdayApache-2.0A85Claude Code
model-selectionawslabs/agent-pluginsSkill937yesterdayApache-2.0A98Claude Code
finetuning-techniqueawslabs/agent-pluginsSkill937yesterdayApache-2.0A87Claude Code
finetuningawslabs/agent-pluginsSkill937yesterdayApache-2.0A85Claude Code