Agent skill

Coding Trace Sanitize

Sanitize normalized coding-trace JSONL rows for public sharing.

Apache-2.0Auto-check: notes

Install Coding Trace Sanitize

skills CLI

$ npx skills add uw-syfi/TraceLab --skill coding-trace-sanitize -a claude-code

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

GitHub CLI

$ gh skill install uw-syfi/TraceLab coding-trace-sanitize --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/uw-syfi/TraceLab.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/coding-trace-sanitize .claude/skills/coding-trace-sanitize && 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/

Paste into Claude Code

Install the "coding-trace-sanitize" agent skill from https://github.com/uw-syfi/TraceLab/tree/main/skills/coding-trace-sanitize into .claude/skills/coding-trace-sanitize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "coding-trace-sanitize", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/uw-syfi/TraceLab/tree/main/skills/coding-trace-sanitize

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add uw-syfi/TraceLab --skill coding-trace-sanitize -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install uw-syfi/TraceLab coding-trace-sanitize --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/uw-syfi/TraceLab.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/coding-trace-sanitize .agents/skills/coding-trace-sanitize && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "coding-trace-sanitize" agent skill from https://github.com/uw-syfi/TraceLab/tree/main/skills/coding-trace-sanitize into .agents/skills/coding-trace-sanitize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "coding-trace-sanitize", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add uw-syfi/TraceLab --skill coding-trace-sanitize -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install uw-syfi/TraceLab coding-trace-sanitize --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/uw-syfi/TraceLab.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/coding-trace-sanitize .cursor/skills/coding-trace-sanitize && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "coding-trace-sanitize" agent skill from https://github.com/uw-syfi/TraceLab/tree/main/skills/coding-trace-sanitize into .cursor/skills/coding-trace-sanitize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "coding-trace-sanitize", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/uw-syfi/TraceLab.git --path skills/coding-trace-sanitize

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add uw-syfi/TraceLab --skill coding-trace-sanitize -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install uw-syfi/TraceLab coding-trace-sanitize --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/uw-syfi/TraceLab.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/coding-trace-sanitize .gemini/skills/coding-trace-sanitize && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "coding-trace-sanitize" agent skill from https://github.com/uw-syfi/TraceLab/tree/main/skills/coding-trace-sanitize into .gemini/skills/coding-trace-sanitize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "coding-trace-sanitize", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install uw-syfi/TraceLab coding-trace-sanitize

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add uw-syfi/TraceLab --skill coding-trace-sanitize -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/uw-syfi/TraceLab.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/coding-trace-sanitize .github/skills/coding-trace-sanitize && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "coding-trace-sanitize" agent skill from https://github.com/uw-syfi/TraceLab/tree/main/skills/coding-trace-sanitize into .github/skills/coding-trace-sanitize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "coding-trace-sanitize", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add uw-syfi/TraceLab --skill coding-trace-sanitize -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install uw-syfi/TraceLab coding-trace-sanitize --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/uw-syfi/TraceLab.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/coding-trace-sanitize .opencode/skills/coding-trace-sanitize && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "coding-trace-sanitize" agent skill from https://github.com/uw-syfi/TraceLab/tree/main/skills/coding-trace-sanitize into .opencode/skills/coding-trace-sanitize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "coding-trace-sanitize", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: coding-trace-sanitize
GitHub stars: 138
Token cost: ~1.3k tokens
SKILL.md length: 422 words
Files: 2
Skills in repo: 7
Repo updated: Aug 22, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Sanitize normalized coding-trace JSONL rows for public sharing.

Works in 4 steps: Work from the coding-trace repo root,… → Confirm the input is a normalized round… → If starting from local histories, run… → …
Preparing trace/llmroundtrace.jsonl outputs for release
SKILL.md covers Overview, First Steps, Main Commands and What The Sanitizer Does, plus 2 more sections
Calls uv and rg

What it does

Coding Trace Sanitize is an agent skill from uw-syfi/TraceLab. Sanitize normalized coding-trace JSONL rows for public sharing. Use when preparing trace/llmroundtrace.jsonl outputs for release, removing local paths, pseudonymizing user identifiers, dropping tools[].input, replacing session/round/tool/project identifiers with stable pseudorandom values, choosing deterministic versus random sanitizer seeds, or checking what sensitive fields remain after sanitizeroundtrace.py.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

The repository describes itself as: An open toolkit and public dataset hub for collecting, sanitizing, analyzing, and visualizing coding agent traces. The licence is Apache-2.0.

When your agent uses it

Preparing trace/llmroundtrace.jsonl outputs for release
Removing local paths
Pseudonymizing user identifiers
Dropping tools[].input

Example prompts

“/coding-trace-sanitize”

Requirements

Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

Work from the coding-trace repo root, identified by pyproject.toml, README.md, and scripts/sanitize_round_trace.py.
Confirm the input is a normalized round trace such as trace/llm_round_trace.jsonl, not an expanded raw example.
If starting from local histories, run $coding-trace-collect first to produce normalized rows.
The default output is stdout; pass -o/--output for files. Use deterministic seeds when comparing versions; use --random-seed when…

What it can do on your machine

Read from SKILL.md and the folder at commit 11b8b14. 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
Shell commands in SKILL.md call:
- uv
- rg
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
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

Coding Trace Sanitize loads about 1.3k tokens when it runs. Until then it costs about 110 tokens; SKILL.md has 422 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~110
When it runs · the whole SKILL.md, loaded when a task matches: ~1.3k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NoteRuns commands with sudoSKILL.md:48

The all-user sudo wrapper can sanitize immediately after collection:

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 uw-syfi/TraceLab at commit 11b8b14, republished under its Apache-2.0 licence (© uw-syfi). 422 words, ~1,273 tokens.

Download SKILL.mdSave it as .claude/skills/coding-trace-sanitize/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: coding-trace-sanitize
description: Sanitize normalized coding-trace JSONL rows for public sharing. Use when preparing trace/llm_round_trace*.jsonl outputs for release, removing local paths, pseudonymizing user identifiers, dropping tools[].input, replacing session/round/tool/project identifiers with stable pseudorandom values, choosing deterministic versus random sanitizer seeds, or checking what sensitive fields remain after sanitize_round_trace.py.

Coding Trace Sanitize

Overview

Use this skill to prepare normalized round traces for sharing. The sanitizer targets the normalized JSONL schema, not arbitrary raw Claude/Codex logs.

First Steps

Work from the coding-trace repo root, identified by pyproject.toml, README.md, and scripts/sanitize_round_trace.py.
Confirm the input is a normalized round trace such as trace/llm_round_trace.jsonl, not an expanded raw example.
If starting from local histories, run $coding-trace-collect first to produce normalized rows.
The default output is stdout; pass -o/--output for files. Use deterministic seeds when comparing versions; use --random-seed when producing a one-off public artifact and stable cross-run ids are not needed.

Main Commands

Sanitize one timestamped private collection without writing loose files at the trace/ root:

bash

collection_directory="trace/collections/<collection_id>"
uv run python scripts/sanitize_round_trace.py \
  "${collection_directory}/merged.private.jsonl" \
  -o "${collection_directory}/merged.public.jsonl"

Use a named deterministic seed:

bash

uv run python scripts/sanitize_round_trace.py \
  "${collection_directory}/merged.private.jsonl" \
  -o "${collection_directory}/merged.public.jsonl" \
  --seed my-release-v1

Use a fresh random seed:

bash

uv run python scripts/sanitize_round_trace.py \
  "${collection_directory}/merged.private.jsonl" \
  -o "${collection_directory}/merged.public.jsonl" \
  --random-seed

The all-user sudo wrapper can sanitize immediately after collection:

bash

scripts/collect_all_users_sudo.sh --sanitize

After sanitizing, use the sanitized output for public analysis and validators:

bash

uv run python artifacts/utils/trace_db.py \
  trace/collections/current/merged.public.jsonl \
  trace/collections/current/merged.public.duckdb
uv run python artifacts/run_all.py \
  --db trace/collections/current/merged.public.duckdb
uv run python validators/run_all.py \
  --db trace/collections/current/merged.public.duckdb

What The Sanitizer Does

scripts/sanitize_round_trace.py performs these transformations:

Replaces project, session_id, turn_id, round_id, tool_call_id, and trace_key with stable pseudorandom alternatives while preserving relationships inside the output.
Replaces user, user_name, and username values with stable pseudonyms while preserving distinct-user counts and grouping.
Removes sensitive local context keys such as cwd, home, host, hostname, file_path, filepath, repo_url, repository_url, session_file, and workdir.
Removes keys ending in path-like forms such as _path, _filepath, or filepath.
Drops tools[].input entirely.
Preserves tools[].input_chars, result_chars, timing, model, provider, token counts, event types, and aggregate structure.
Rewrites timing_events[].tool_call_id consistently with the corresponding tool id.
Prints a short rows=... tools=... output=... seed=... status line to stderr.

Show full SKILL.md (169 more words)Show less

What It Does Not Guarantee

Do not claim the sanitizer proves a trace is safe for every release context. It does not inspect semantic leakage in model names, visible text summaries, tool names, timing patterns, token counts, or result sizes. It also does not sanitize arbitrary raw provider logs.

If the user wants to share raw examples, inspect or create public raw examples separately using $coding-trace-raw; do not run the normalized sanitizer on expanded raw text and assume it worked.

Verification

After sanitizing, run a shape summary:

bash

uv run python artifacts/utils/trace_db.py \
  trace/collections/current/merged.public.jsonl \
  trace/collections/current/merged.public.duckdb
uv run python artifacts/trace_facts/overview_summary/analyze.py \
  --db trace/collections/current/merged.public.duckdb --json

Use targeted searches for obvious leftovers:

bash

rg -n '"(cwd|home|session_file|workdir)"' "${collection_directory}/merged.public.jsonl"

bash

rg -n '"input":' "${collection_directory}/merged.public.jsonl"

Empty search output is a useful smoke test, not a complete privacy audit. user fields are expected to remain, but their values should look like user_<hex>. When reporting results, state the sanitizer's exact scope and any remaining review risk.

For an end-to-end smoke test, materialize the sanitized file once and run the artifact and validator dispatchers against that DuckDB. The artifact dispatcher derives the local timing-fit CSV from the same database before timing analyses consume it.

Files

SKILL.md and 1 other file in skills/coding-trace-sanitize of uw-syfi/TraceLab.

SKILL.md
agents/openai.yaml

Open the folder on GitHubat commit 11b8b14

Compare with similar skills

Coding Trace Sanitize 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.

Coding Trace Sanitize compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Coding Trace Sanitize this skilluw-syfi/TraceLab	138	—	~1.3k	Automated safety check: Notes	Apache-2.0	1 mo ago
ShareClickHouse/ClickHouse	50k	—	~558	Automated safety check: Notes	Apache-2.0	today
Observe Traceruvnet/ruflo	74k	—	~522	Automated safety check: Notes	MIT	today
SharingBuilderIO/agent-native	7.1k	—	~3.4k	Automated safety check: Pass	None	today
Tracezereight/gitlab-mcp	2k	1 repos	~412	Automated safety check: Pass	MIT	2 days ago
Deslop Shared Libsgarrytan/gstack	136k	—	~3.3k	Automated safety check: Notes	MIT	today

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Questions about Coding Trace Sanitize

What does Coding Trace Sanitize do?

Sanitize normalized coding-trace JSONL rows for public sharing. Coding Trace Sanitize is an agent skill from uw-syfi/TraceLab. Sanitize normalized coding-trace JSONL rows for public sharing.

When should I use Coding Trace Sanitize?

Coding Trace Sanitize fits situations like: preparing trace/llmroundtrace.jsonl outputs for release; removing local paths; pseudonymizing user identifiers; dropping tools[].input.

How do I install Coding Trace Sanitize in Claude Code?

Run `npx skills add uw-syfi/TraceLab --skill coding-trace-sanitize -a claude-code`. Or copy the skill folder (skills/coding-trace-sanitize in uw-syfi/TraceLab) into .claude/skills/coding-trace-sanitize in your project. Claude Code loads it when a task matches its description.

How do I install Coding Trace Sanitize in Codex?

Run `npx skills add uw-syfi/TraceLab --skill coding-trace-sanitize -a codex`. Or copy the skill folder (skills/coding-trace-sanitize in uw-syfi/TraceLab) into .agents/skills/coding-trace-sanitize in your project. Codex loads it when a task matches its description.

Can I use Coding Trace Sanitize 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 uw-syfi/TraceLab --skill coding-trace-sanitize -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/coding-trace-sanitize, .gemini/skills/coding-trace-sanitize, .github/skills/coding-trace-sanitize and .opencode/skills/coding-trace-sanitize in your project.

What does Coding Trace Sanitize need to run?

Going by SKILL.md and its folder, Coding Trace Sanitize needs the command-line tools its instructions call (uv and rg). Our summary lists: Python 3.

Does Coding Trace Sanitize access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Coding Trace Sanitize safe to install?

Our automated static check of SKILL.md found notes only (runs commands with sudo), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Coding Trace Sanitize use?

Coding Trace Sanitize is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Coding Trace Sanitize use?

About 1.3k tokens (SKILL.md is roughly 5.1k 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 Coding Trace Sanitize?

Skills that share tags, products or a category with Coding Trace Sanitize: Share (ClickHouse/ClickHouse, 50k stars), Observe Trace (ruvnet/ruflo, 74k stars), Sharing (BuilderIO/agent-native, 7.1k stars) and Trace (zereight/gitlab-mcp, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Coding Trace Sanitize?

uw-syfi (a GitHub organization) maintains it in uw-syfi/TraceLab, which has 138 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on August 22, 2026.

Source: uw-syfi/TraceLab on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Coding Trace Sanitize

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Coding Trace Sanitize

Overview

First Steps

Main Commands

What The Sanitizer Does

What It Does Not Guarantee

Verification

Files

Compare with similar skills

Similar skills

More from uw-syfi/TraceLab

Questions about Coding Trace Sanitize