Hackenproof Report Handoff logo

Hackenproof Report Handoff

Organization
hackenproof-public
hackenproof-report-handoff

Generate structured report handoff summaries for client teams. Use after triaging a report to produce a standardized handoff with report URL, recommended severity, bounty range, and explanation. Trigger on "handoff", "transfer to client", "prepare handoff", "client summary".

Overview

Publisherhackenproof-public
Repositoryskills
Skill namehackenproof-report-handoff
Stars
52
Forks
13
Bundled files
2
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hackenproof-public on GitHub. Read the source before you install it.

Installation

Install the Hackenproof Report Handoff AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hackenproof-public/skills/tree/main/plugins/hackenproof-handoff/skills/hackenproof-report-handoff
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hackenproof-public/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/hackenproof-handoff/skills/hackenproof-report-handoff .claude/skills/hackenproof-report-handoff
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hackenproof Report Handoff in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hackenproof Report Handoff on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hackenproof Report Handoff is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

HackenProof Report Handoff

Generate a structured handoff summary after triaging a report. The handoff is what gets communicated to the client team — it must be clear, actionable, and include bounty context.

When to Use

  • After a report has been triaged (state is Triaged or any final state)
  • When preparing a batch of triaged reports for client review
  • When a client team requests a summary of findings

Workflow

  1. Run get_program_info to retrieve reward ranges, scopes, and program type.
  2. Run get_report_details with full=true to get the complete report.
  3. Extract the reward range for the report's severity from program rewards.
  4. Generate the handoff summary using the template from references/handoff-template.md.
  5. If multiple reports are provided, generate one handoff per report.

Mandatory Tool Sequence

  1. Call get_program_info — extract rewards object to map severity to bounty range.
  2. Call get_report_details — extract title, severity, state, vulnerability description, target, and CVSS score.
  3. If severity has not been set yet, recommend one using references/severity-to-bounty.md and program rewards.
  4. Build the report URL from company, program, and report_id.
  5. Produce the handoff in the exact format from references/handoff-template.md.

Output Rules

  • Always include the full dashboard URL.
  • Always include both recommended severity AND bounty range (even if it's "$0" for informational).
  • Keep the summary to 2-3 sentences max — focus on what the vulnerability is, what it impacts, and what the client should do.
  • If the report is a duplicate, mention the duplication group but do NOT reference the original report ID (reporter cannot see it).
  • If bounty range is not available in program info, state "Bounty range not configured for this severity" instead of guessing.

Batch Mode

When given multiple report IDs:

  1. Fetch program info once (shared across all reports).
  2. Use get_reports_details_batch for efficiency.
  3. Output handoffs sorted by severity (Critical first, then High, Medium, Low).
  4. Add a summary line at the top: "X reports: Y Critical, Z High, ..."

Quality Bar

  • Every handoff must be grounded in actual report data — never fabricate impact or severity.
  • Bounty range must come from get_program_info rewards, not from memory or assumptions.
  • If the report lacks enough detail for a clear summary, note what's missing.
  • Keep tone professional and neutral — this goes to the client.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Hackenproof Report Handoff AI skill do?

Generate structured report handoff summaries for client teams. Use after triaging a report to produce a standardized handoff with report URL, recommended severity, bounty range, and explanation. Trigger on "handoff", "transfer to client", "prepare handoff", "client summary".

Why use Hackenproof Report Handoff on TypingMind?

Because you install it once and use it with any model. Hackenproof Report Handoff is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hackenproof Report Handoff in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hackenproof-public/skills/tree/main/plugins/hackenproof-handoff/skills/hackenproof-report-handoff. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Hackenproof Report Handoff?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hackenproof Report Handoff?

As many as you like. As long as a model supports skills, you can use Hackenproof Report Handoff with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hackenproof Report Handoff AI skill free?

It is published on GitHub by hackenproof-public. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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