How do I install the Jev Logscan skill?

Run npx skillmds@latest add wanlanglin/jev-logscan in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Jev Logscan safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Jev Logscan?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Jev Logscan free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Jev Logscan?

WanLanglin (@wanlanglin) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Jev Logscan by wanlanglin — Agent Skill

Name: Jev Logscan
Rating: 4.2 (5 reviews)
Author: WanLanglin

Jev Logscan

Pull the handful of lines that matter out of a long command output, keeping them in their original order. Use when a test run, build, install, CI job, or training loop dumps hundreds or thousands of lines and you need the few that answer a specific question — why it failed, where it got slow, what changed, what ran out of memory. Say what you are looking for with --goal; the ranking is conditioned on it, so the same log returns different lines for different questions. Do NOT use for short output you can just read, or for structured data (JSON, CSV) where you want a parser rather than a filter.

WanLanglin Updated Sep 22, 2026

File contents

jev-logscan

A build just printed 17,000 lines and six of them explain the failure. Reading all of it costs your context; scrolling for the error costs your turn.

Use it

pytest -v 2>&1 | python3 "$CLAUDE_SKILL_DIR/../../scripts/logscan.py" \
  --goal "find out which test failed and why"

python3 .../logscan.py --log build.log --goal "find out why the link step failed"
python3 .../logscan.py --log train.log --goal "find where loss became NaN" --budget 60

--goal is the whole interface. The ranking is conditioned on it, so ask for what you actually want:

"why did this fail" → errors, tracebacks, the failing assertion
"where did it get slow" → timings and durations, not errors
"what configuration was used" → the settings echoed at startup
"what ran out of memory" → allocation and OOM lines

Same log, different lines out.

Reading the output

Lines come back in their original order, with elided runs marked, because a log read out of sequence is unusable. Original line numbers are preserved so you can go back to the source. A ! marks a line that matched an error shape (traceback, SyntaxError:, FAILED, panic:) and was kept regardless of score.

If nothing in the log addresses your goal, it says so instead of padding the output with the least-bad lines.

How it decides

Logs are templated — a build prints Compiling './x'... seventeen thousand times — so lines are collapsed to their shape first (paths, numbers and hashes normalised away), each distinct shape is scored once, then expanded back. On a 17,591-line build log that is 24 distinct shapes, which is why this is fast and cheap on logs that would otherwise be enormous.

Three signals combine: goal relevance from Jev, rarity (a shape seen once matters more than one seen 17,000 times), and error shape as a floor that catches crashes whatever you asked for.

Flags

--budget N — keep at most N lines, best first. Without it, everything above --keep-floor (default 0.10, the measured noul floor) is kept.
--no-always — stop force-keeping error-shaped lines.
--no-jev — rarity and error shape only, no network, no key.
--json — machine-readable, with per-line scores and original line numbers.

Under 40 lines the script just echoes the input; short logs do not need this.

Setup

export TYPESAFE_API_KEY=...   # https://typesafe.ai

---name: jev-logscandescription: Pull the handful of lines that matter out of a long command output, keeping them in their original order. Use when a test run, build, install, CI job, or training loop dumps hundreds or thousands of lines and you need the few that answer a specific question — why it failed, where it got slow, what changed, what ran out of memory. Say what you are looking for with --goal; the ranking is conditioned on it, so the same log returns different lines for different questions. Do NOT use for short output you can just read, or for structured data (JSON, CSV) where you want a parser rather than a filter.license: MIT---# jev-logscanA build just printed 17,000 lines and six of them explain the failure. Readingall of it costs your context; scrolling for the error costs your turn.## Use it```bashpytest -v 2>&1 | python3 "$CLAUDE_SKILL_DIR/../../scripts/logscan.py" \ --goal "find out which test failed and why"``````bashpython3 .../logscan.py --log build.log --goal "find out why the link step failed"python3 .../logscan.py --log train.log --goal "find where loss became NaN" --budget 60```**`--goal` is the whole interface.** The ranking is conditioned on it, so askfor what you actually want:- `"why did this fail"` → errors, tracebacks, the failing assertion- `"where did it get slow"` → timings and durations, not errors- `"what configuration was used"` → the settings echoed at startup- `"what ran out of memory"` → allocation and OOM linesSame log, different lines out.## Reading the outputLines come back **in their original order**, with elided runs marked, because alog read out of sequence is unusable. Original line numbers are preserved so youcan go back to the source. A `!` marks a line that matched an error shape(traceback, `SyntaxError:`, `FAILED`, `panic:`) and was kept regardless of score.If nothing in the log addresses your goal, it says so instead of padding theoutput with the least-bad lines.## How it decidesLogs are templated — a build prints `Compiling './x'...` seventeen thousandtimes — so lines are collapsed to their shape first (paths, numbers and hashesnormalised away), each distinct shape is scored once, then expanded back. On a17,591-line build log that is 24 distinct shapes, which is why this is fast andcheap on logs that would otherwise be enormous.Three signals combine: **goal relevance** from Jev, **rarity** (a shape seenonce matters more than one seen 17,000 times), and **error shape** as a floorthat catches crashes whatever you asked for.## Flags- `--budget N` — keep at most N lines, best first. Without it, everything above `--keep-floor` (default `0.10`, the measured noul floor) is kept.- `--no-always` — stop force-keeping error-shaped lines.- `--no-jev` — rarity and error shape only, no network, no key.- `--json` — machine-readable, with per-line scores and original line numbers.Under 40 lines the script just echoes the input; short logs do not need this.## Setup```bashexport TYPESAFE_API_KEY=... # https://typesafe.ai```

Frequently asked questions