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Install in OpenClaw
/install support-to-repro-pack
Description
Convert support tickets, logs, and screenshots into sanitized, reproducible engineering issue packs
Usage Guidance
This package looks coherent for converting tickets/logs into sanitized repro packs, but check these before installing/using: 1) Verify screenshot/OCR handling — SKILL.md expects image text extraction but the visible code lacks an OCR dependency; confirm how images will be processed and whether platform vision features or extra libraries are required. 2) Install from a trusted local copy (pip install -e /path) rather than running arbitrary remote installs. 3) Run the CLI in audit mode (repro-pack redact --audit) and review 8_redaction_report.json to validate that sensitive fields are detected and replaced; do not assume 100% coverage — test with representative samples. 4) Inspect omitted/remaining files (the manifest truncated 41 files) for any network calls or unexpected endpoints before running on sensitive data. 5) Use an isolated environment (virtualenv/container) when processing sensitive logs/secrets, and avoid uploading raw inputs to third-party services. 6) Confirm template paths and that the .claude/skills templates referenced by the renderer exist in your deployment layout so rendering works as expected.
Capability Analysis
Type: OpenClaw Skill
Name: support-to-repro-pack
Version: 1.0.0
The support-to-repro-pack skill is a legitimate utility designed to automate the creation of sanitized engineering issue reports from support tickets and logs. The bundle includes a Python backend (src/repro_pack/) that performs deterministic PII redaction using extensive regex patterns (patterns.py), extracts environment facts, and builds event timelines. The SKILL.md instructions guide the AI agent to use these tools to protect customer privacy, specifically instructing it to never output raw PII or internal details in customer-facing documents. No evidence of data exfiltration, unauthorized network access, or malicious execution was found; the code is well-structured, transparent, and includes a comprehensive test suite.
Capability Assessment
Purpose & Capability
Name/description match the codebase: there is a deterministic Python backend (redactor, parsers, extractors, packager, CLI) that implements PII redaction, log parsing, stack-trace extraction, facts/timeline extraction and packaging. The SKILL.md instructions to run the Python tools (python -m repro_pack ...) align with the packaged CLI and pipeline.
Instruction Scope
SKILL.md tells the agent to read user-provided files (tickets, log paths, screenshots), save pasted text to temp files, run the CLI tooling, and produce outputs. Reading files and running local tools is expected for this task. One gap: SKILL.md instructs explicit image processing/OCR ("extract all visible text" from screenshots) but the visible Python modules in the manifest don't show an OCR/image-processing dependency or implementation (e.g., pytesseract, PIL, or a vision module) — either these files are among the truncated ones or the agent is expected to use platform vision capabilities. Confirm how screenshots are handled before relying on automatic image OCR.
Install Mechanism
No install spec in the registry (instruction-only skill) but the repo includes a Python package and SKILL.md asks to pip install -e /path/to/support-to-repro-pack. That is reasonable for local use, but there's no remote release host or package publisher declared; you must install from a local path. No external download URLs or installers were present in the provided manifest.
Credentials
The skill requests no environment variables, no credentials, and no config paths. The code itself scans for many PII patterns (AWS keys, JWTs, Stripe keys, etc.) which is appropriate for a redaction tool. There are no declared credentials or unrelated environment access requests.
Persistence & Privilege
Flags: always is false and model invocation is allowed by default. The skill does not request permanent system-wide presence or modify other skills. It writes output files and a validation report in the specified output directory — this is expected behavior for a packager.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install support-to-repro-pack - After installation, invoke the skill by name or use
/support-to-repro-pack - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of support-to-repro-pack skill.
- Converts support tickets, logs, and screenshots into sanitized, reproducible engineering issue packs.
- Guides user through input collection, PII redaction, structured log analysis, and AI review steps.
- Generates three output documents: engineering issue, internal escalation summary, and customer reply.
- Automates packaging of all sanitized artifacts for engineering handoff.
- Enforces strict PII handling and language matching based on user input.
Metadata
Frequently Asked Questions
What is support-to-repro-pack?
Convert support tickets, logs, and screenshots into sanitized, reproducible engineering issue packs. It is an AI Agent Skill for Claude Code / OpenClaw, with 129 downloads so far.
How do I install support-to-repro-pack?
Run "/install support-to-repro-pack" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is support-to-repro-pack free?
Yes, support-to-repro-pack is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does support-to-repro-pack support?
support-to-repro-pack is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created support-to-repro-pack?
It is built and maintained by mshs01156 (@mshs01156); the current version is v1.0.0.
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