Plugins

1 plugin

Results for “log-analysis”

13 skills
More results
machenjie
Unit Testing
`analysis-agent`/`task-agent`/`review-agent`: use when logic, rules, invariants, branches, edges, or failure paths need isolated tests; skip without a unit-test decision.
4 · bundle
ziri22
Agent Logging V2
Expert en logging v2 (ELK, Loki, Fluentd, structured logging, correlation IDs, alerting)
6
brycewang-stanford
Stata Log
Tail, read, or search a Stata log file from a previous command or background task.
1k · bundle
landonschropp
Identify Skill Gaps
Use when analyzing Claude Code conversation logs to find patterns in repeated user instructions that could become skills. Ask for date range first.
1 · bundle
machenjie
Service Business Logic
`analysis-agent`/`task-agent`: use when a use case coordinates authorization, domain work, transactions, or external effects; skip transport, storage, and rule-only work.
4 · bundle
qhjqhj00
Ara Compiler
Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a.
3 · bundle
srednoff888-art
Crawler Analyst Agent
Use this skill for crawler behavior, log files, sitemap/indexation analysis, crawl-budget diagnostics. Trigger when the task involves agent profile work related to Crawler Analyst Agent, implementation, audits, debugging, strategy, or validation.
1 · bundle
addyosmani
Browser Testing With Devtools
Tests and debugs web applications in real browsers using Chrome DevTools MCP, enabling DOM inspection, console error capture, network analysis, performance profiling, and visual verification with live runtime data.
69.5k
schattenspiegel
Arviz Python
Use for writing, reviewing, debugging, or testing Python analysis of Bayesian inference results with ArviZ, including 1.x DataTree groups, legacy InferenceData inputs, xarray dimensions and coordinates, conversion, summaries, R-hat/ESS/MCSE diagnostics, posterior predictive checks, PSIS-LOO, Pareto-k, and model comparison. Trigger on chain/draw shape errors, mislabeled groups, flattened samples, missing log likelihood, or misleading diagnostic claims. Do not use to construct or sample PyMC, NumPyro, or Bambi models, for generic plotting, or for deterministic statistics without Bayesian draws.
0 · bundle