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ai-app-instrumentation

Instrument a GenAI application — any language, provider, framework, and maturity from no OpenTelemetry to a production collector — with OpenTelemetry GenAI spans, get it running, and verify it renders in Coralogix AI Center. Use when asked to send LLM, AI or agent traces to Coralogix, add gen_ai instrumentation, connect an AI app or agent to AI Center, or when an app is missing from AI Center or shows no cost or prompts. Not for Claude Code / Cursor CLI telemetry (the Code Agents screen), zero-code eBPF capture, or whole-service APM — use opentelemetry-instrumentation or opentelemetry-collector for those.

71

Quality

89%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Outstanding actionability and workflow rigor — executable queries, gated verification with a real feedback loop, and symptom-driven debugging — undermined only by its monolithic, token-heavy presentation. Splitting the Stacks table, Pitfalls, and cx CLI reference into bundle files and deduplicating cross-section repetition would raise both conciseness and progressive disclosure without losing any guidance.

Suggestions

Move the Stacks instrumentor table, the Pitfalls table, and the cx CLI reference into references/ files (e.g. references/stacks.md, references/pitfalls.md, references/cx-cli.md), keeping only a routing summary and the most common cases inline in SKILL.md.

Deduplicate repeated guidance: the LiteLLM streamed-calls known issue is stated verbatim in two Stacks rows and again in Pitfalls — state it once and cross-reference; the provider well-known-value table appears in both the Implementation section and the Stacks Notes — keep a single source of truth.

Consolidate the switch-wiring rule ('wire ON in each environment's config file, cite file:line') that currently appears in Rules 9, the Instrument Principles, the Run shared contract, and the Pitfalls table into one authoritative statement with pointers.

DimensionReasoningScore

Conciseness

The ~660-line body never pads with concepts Claude already knows, but there is real redundancy: the LiteLLM streamed-calls known issue appears verbatim in two Stacks rows and again in Pitfalls; the provider well-known-value table appears in both Implementation and the Stacks Notes; switch-wiring-with-file:line guidance is repeated across Rules 9, the Principles section, the Run checklist, and Pitfalls. This fits the 3 anchor ('mostly efficient … could be tightened'); it is not a 4 because several sections duplicate each other wholesale, and not a 2 because it assumes competence and adds no beginner-level explanation.

3 / 5

Actionability

Fully executable throughout: a copy-paste canonical `cx spans` query set, a complete collector YAML config, per-stack instrumentor names with versions and exact content-capture env vars, and concrete probe/wait commands with Bash timeout mechanics. Matches the 5 anchor (copy-paste ready, covers common cases).

5 / 5

Workflow Clarity

Four phases each with explicit input/output contracts and pause points, a maturity router, and a 12-gate verification table with per-gate PASS criteria and required evidence — plus an explicit feedback loop (MUST FAIL → gap list → back to Instrument → re-run → re-verify) and a 48-row symptom/cause/fix Pitfalls table. Textbook validation checkpoints with error recovery.

5 / 5

Progressive Disclosure

Good internal section structure with headers and tables, but the skill is entirely monolithic — no references/, scripts/, or assets/ exist, and content that clearly belongs in separate files is inlined: the ~30-row Stacks instrumentor table, the 48-row Pitfalls table, and the cx CLI reference would each be natural bundle files loaded on demand. This fits the 3 anchor ('some structure … content that should be separate is inline'); not a 4 because no content at all is offloaded, and not a 2 because navigation within the file is clear.

3 / 5

Total

16

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A model description: concrete third-person actions, comprehensive natural-language triggers for both intent-based and symptom-based requests, and explicit disambiguation from sibling skills. It answers what, when, and when-not with no padding.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Instrument a GenAI application … with OpenTelemetry GenAI spans, get it running, and verify it renders in Coralogix AI Center' — plus explicit scope ('any language, provider, framework, and maturity from no OpenTelemetry to a production collector') and negative scope. This matches the 5 anchor ('multiple specific concrete actions; comprehensive coverage'); a 4 would require minor coverage gaps, and none are evident.

5 / 5

Completeness

Explicitly answers both 'what' (instrument with gen_ai spans, get it running, verify rendering in AI Center) and 'when' ('Use when asked to send LLM, AI or agent traces to Coralogix… or when an app is missing from AI Center or shows no cost or prompts') with concrete trigger phrases — the exact 5-anchor pattern. The explicit 'Not for…' clause further sharpens the boundary.

5 / 5

Trigger Term Quality

Natural user phrasings are comprehensive: 'send LLM, AI or agent traces to Coralogix', 'add gen_ai instrumentation', 'connect an AI app or agent to AI Center', 'app is missing from AI Center or shows no cost or prompts' — covering symptom-based triggers users would actually say, not just jargon.

5 / 5

Distinctiveness Conflict Risk

Clear niche (Coralogix AI Center gen_ai span instrumentation) with minimal conflict risk: adjacent skills are named and carved out ('Not for Claude Code / Cursor CLI telemetry (the Code Agents screen), zero-code eBPF capture, or whole-service APM — use opentelemetry-instrumentation or opentelemetry-collector for those').

5 / 5

Total

20

/

20

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (695 lines); consider splitting into references/ and linking

Warning

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

metadata_field

'metadata' should map string keys to string values

Warning

Total

13

/

16

Passed

Repository

coralogix/cx-skills

Path

skills/ai-center/ai-app-instrumentation/SKILL.md

Reviewed

Table of Contents

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