Agent skill

Observability Analyzer

by majiayu000 in majiayu000/claude-skill-registry

Query and analyze Claude Code observability data (metrics, logs, traces).

MITAuto-check passedDevOps & Cloud

Install Observability Analyzer

skills CLI
$ npx skills add majiayu000/claude-skill-registry --skill observability-analyzer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/claude-skill-registry observability-analyzer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analysis/observability-analyzer .claude/skills/observability-analyzer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
observability-analyzer
GitHub stars
666
Used in
1 other repo
Token cost
~1.6k tokens
SKILL.md length
353 words
Files
2
Skills in repo
971
Repo updated
First seen
Licence
MIT

At a glance

Query and analyze Claude Code observability data (metrics, logs, traces).

  • Analyzing performance
  • SKILL.md covers Data Sources, Operations, Key Queries and Event Types Reference, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve Observability

What it does

Observability Analyzer is an agent skill from majiayu000/claude-skill-registry. Query and analyze Claude Code observability data (metrics, logs, traces). Use when analyzing performance, costs, errors, tool usage, sessions, conversations, or subagents.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It sits in DevOps & Cloud, covering Observability, Subagents and Monitoring and alerting. It works with Prometheus and OpenTelemetry. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

When your agent uses it

  • Analyzing performance
  • Tasks that involve Observability
  • Tasks that involve Subagents

Example prompts

  • “/observability-analyzer”

What it can do on your machine

Read from SKILL.md and the folder at commit 000116a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are logql, bash and promql).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Observability Analyzer loads about 1.6k tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 353 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~49
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 000116a, republished under its MIT licence (© majiayu000). 353 words, ~1,636 tokens.

Download SKILL.mdSave it as .claude/skills/observability-analyzer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
observability-analyzer
description
Query and analyze Claude Code observability data (metrics, logs, traces). Use when analyzing performance, costs, errors, tool usage, sessions, conversations, or subagents.

Observability Analyzer

Query Claude Code telemetry and generate insights from metrics, logs, and traces. Works with both default OTEL telemetry and enhanced hook-based telemetry.

Data Sources

SourceJob NameContains
Default OTELclaude_codeAPI metrics, token usage, costs
Enhanced Hooksclaude_code_enhancedSessions, conversations, tools, subagents

Operations

query-metrics <promql>

Execute PromQL query against Prometheus.

bash
query-metrics 'sum(claude_code_token_usage)[7d]'
query-logs <logql>

Execute LogQL query against Loki.

bash
query-logs '{job="claude_code_enhanced", event_type="tool_call"} | json' --since 24h
analyze-errors

Detect and group error patterns from enhanced telemetry.

logql
{job="claude_code_enhanced", event_type="tool_result", status="error"} | json

Output: Error types, frequencies, affected tools, recommendations.

analyze-performance

Identify slow operations and response sizes.

logql
{job="claude_code_enhanced", event_type="tool_result"} | json | response_length > 50000

Output: Large responses, estimated token costs, slow patterns.

analyze-costs

Calculate token usage from content size estimates.

logql
sum by (repo) (sum_over_time({job="claude_code_enhanced", event_type="context_utilization"} | json | unwrap estimated_session_tokens [24h]))

Output: Token estimates by repo, session costs, projections.

analyze-tools

Tool usage statistics and sequences.

logql
sum by (tool) (count_over_time({job="claude_code_enhanced", event_type="tool_call"} | json [24h]))

Output: Call frequency, success rates, tool sequences, common patterns.

analyze-sessions

Session lifecycle and duration analytics.

logql
{job="claude_code_enhanced", event_type="session_end"} | json

Output: Session durations, turn counts, tools per session, termination reasons.

analyze-conversations

Conversation and prompt analytics.

logql
sum by (pattern) (count_over_time({job="claude_code_enhanced", event_type="user_prompt"} | json [24h]))

Output: Prompt patterns (question/debugging/creation/ultrathink), turn distribution.

analyze-subagents

Subagent/Task tool usage.

logql
{job="claude_code_enhanced", event_type="tool_call", tool="Task"} | json

Output: Subagent types used, completion rates, parallel execution patterns.

analyze-skills

Skill invocation analytics.

logql
sum by (skill_name) (count_over_time({job="claude_code_enhanced", event_type="skill_usage"} | json [24h]))

Output: Most used skills, skill usage by repo, trends.

analyze-context

Context window utilization.

logql
{job="claude_code_enhanced", event_type="context_utilization"} | json | context_percentage > 50

Output: High utilization sessions, compaction events, token efficiency.

analyze-repos

Repository/project activity.

logql
sum by (repo, tool) (count_over_time({job="claude_code_enhanced", event_type="tool_call"} | json [24h]))

Output: Activity per repo, tool usage by project, branch patterns.

generate-report

Comprehensive analysis report (all dimensions). Output: Markdown report with errors, performance, costs, sessions, conversations, tools.

Show full SKILL.md (137 more words)Show less

Key Queries

Enhanced Telemetry (Loki)
logql
# All events (last hour)
{job="claude_code_enhanced"} | json

# Session analytics
{job="claude_code_enhanced", event_type="session_end"} | json | duration_seconds > 300

# Tool errors
{job="claude_code_enhanced", event_type="tool_result", status="error"} | json

# High context usage
{job="claude_code_enhanced", event_type="context_utilization"} | json | context_percentage > 75

# Subagent spawns
{job="claude_code_enhanced", event_type="tool_call", tool="Task"} | json

# Skill invocations
{job="claude_code_enhanced", event_type="skill_usage"} | json

# Prompt patterns
{job="claude_code_enhanced", event_type="user_prompt"} | json | pattern="ultrathink"

# Tool sequences
{job="claude_code_enhanced", event_type="tool_call"} | json | line_format "{{.tool_name}} → {{.previous_tool}}"

# Context compaction
{job="claude_code_enhanced", event_type="context_compact"} | json

# Permission requests
{job="claude_code_enhanced", event_type="permission_request"} | json
Default OTEL (Prometheus)
promql
# Total token usage (7 days)
sum(increase(claude_code_token_usage[7d]))

# Error rate by tool
sum by (tool_name) (rate(claude_code_tool_result{status="failure"}[1h]))

# P95 tool latency
histogram_quantile(0.95, claude_code_tool_duration_bucket)

# Daily costs
sum(increase(claude_code_cost_usage[24h]))

Event Types Reference

Event TypeDescriptionKey Fields
session_startSession initializationsource, permission_mode
session_endSession terminationduration_seconds, turn_count, tools_used
user_promptUser message submittedpattern, prompt_length, estimated_tokens
tool_callTool invocationtool_name, tool_details, sequence_position
tool_resultTool completionstatus, response_length, is_error
skill_usageSkill invokedskill_name
context_utilizationToken estimateestimated_session_tokens, context_percentage
context_compactCompaction eventtrigger (manual/auto)
subagent_completeTask agent finishedtotal_subagents
permission_requestPermission dialognotification_type
notificationSystem notificationnotification_type

Grafana Dashboards

  • Claude Code Overview - High-level metrics
  • Tool Performance - Tool latencies and success rates
  • Cost Analysis - Token usage and costs
  • Error Tracking - Error patterns and trends
  • Session Analytics - Session-level insights
  • Enhanced Analytics - Model/skill/context/repo tracking
  • Deep Analytics - Comprehensive conversation and tool analysis

Access: http://localhost:3000 (admin/admin)

Scripts

  • scripts/query-prometheus.sh - PromQL query helper
  • scripts/query-loki.sh - LogQL query helper
  • scripts/analyze-errors.sh - Error analysis automation
  • scripts/analyze-sessions.sh - Session analytics
  • scripts/generate-report.sh - Full analysis report

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/analysis/observability-analyzer of majiayu000/claude-skill-registry.

  • SKILL.md
  • metadata.json

Open the folder on GitHubat commit 000116a

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Observability Analyzer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Observability Analyzer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Observability Analyzer this skillmajiayu000/claude-skill-registry6661 repos~1.6kAutomated safety check: PassMIT
Developing Funboost Mixinydf0509/funboost892—~2.1kAutomated safety check: PassNone
Archestra Dev Observabilityarchestra-ai/archestra4.3k—~1.2kAutomated safety check: PassCustom licence
Frontmcp Observabilityagentfront/frontmcp146—~4.6kAutomated safety check: PassApache-2.0
Monitoring Observabilityahmedasmar/devops-claude-skills203—~3.9kAutomated safety check: PassNone
Observability Architecturemajiayu000/litellm-rs116—~1.3kAutomated safety check: PassMIT

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Categories

Questions about Observability Analyzer

What does Observability Analyzer do?

Query and analyze Claude Code observability data (metrics, logs, traces). Observability Analyzer is an agent skill from majiayu000/claude-skill-registry. Query and analyze Claude Code observability data (metrics, logs, traces).

When should I use Observability Analyzer?

Observability Analyzer fits situations like: analyzing performance; tasks that involve Observability; tasks that involve Subagents.

How do I install Observability Analyzer in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill observability-analyzer -a claude-code`. Or copy the skill folder (skills/analysis/observability-analyzer in majiayu000/claude-skill-registry) into .claude/skills/observability-analyzer in your project. Claude Code loads it when a task matches its description.

How do I install Observability Analyzer in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill observability-analyzer -a codex`. Or copy the skill folder (skills/analysis/observability-analyzer in majiayu000/claude-skill-registry) into .agents/skills/observability-analyzer in your project. Codex loads it when a task matches its description.

Can I use Observability Analyzer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill observability-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/observability-analyzer, .gemini/skills/observability-analyzer, .github/skills/observability-analyzer and .opencode/skills/observability-analyzer in your project.

What does Observability Analyzer need to run?

SKILL.md names no scripts, command-line tools or credentials: Observability Analyzer is instructions for the agent only.

Does Observability Analyzer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Observability Analyzer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Observability Analyzer use?

Observability Analyzer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Observability Analyzer use?

About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Observability Analyzer?

Skills that share tags, products or a category with Observability Analyzer: Developing Funboost Mixin (ydf0509/funboost, 892 stars), Archestra Dev Observability (archestra-ai/archestra, 4.3k stars), Frontmcp Observability (agentfront/frontmcp, 146 stars) and Monitoring Observability (ahmedasmar/devops-claude-skills, 203 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Observability Analyzer?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 971 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.