A structured bug bounty report writer for platforms such as HackerOne, Bugcrowd, Intigriti, and Immunefi. It turns a validated security finding into a report with reproduction steps, impact, severity scoring, and a suggested fix.

Use it to prepare a submission from an affected endpoint, test requests and responses, accounts, bug class, and technology details.

It removes the work of formatting a finding for different reporting platforms and helps make the evidence and impact clear. It requires validation first so unsupported findings are not submitted.

report — Command for Claude Code by adriannoes

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo

git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/commands/adriannoes/awesome-agentic-ai/report.svg)](https://agentmods.dev/commands/adriannoes/awesome-agentic-ai/report)

Your own site

<a href="https://agentmods.dev/commands/adriannoes/awesome-agentic-ai/report"><img src="https://agentmods.dev/badge/commands/adriannoes/awesome-agentic-ai/report.svg" alt="Measured on agentmods" height="20"></a>

Per session 52 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 926 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 86% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00052	$0.00926
Opus 5	$0.00026	$0.00463
Sonnet 5	$0.00010	$0.00185
Haiku 4.5	$0.00005	$0.00093

Measured 4d ago against content hash 8dc2ab489c16, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

86% identical to report — 22 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

cursor-claude-codex/skills/bug-hunter/commands/report.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/report

Generate a submission-ready bug bounty report.

Pre-Conditions

Run /validate first. All 4 gates must pass before running this command.

Never write a report before validating. N/A submissions hurt your validity ratio.

Usage

/report

Provide when prompted:

Platform (HackerOne / Bugcrowd / Intigriti / Immunefi)
Bug class
Affected endpoint
Your two test accounts and their IDs
The exact HTTP request that demonstrates the bug
The exact response that shows the impact
Tech stack (for CVSS and remediation advice)

What This Generates

Title following the formula: [Bug Class] in [Endpoint] allows [actor] to [impact]
Summary paragraph (impact-first, no "could potentially")
Vulnerability details with CVSS 3.1 score and vector string
Steps to Reproduce with copy-paste HTTP requests
Impact statement with quantification
Recommended fix (1-2 sentences, specific)
Supporting materials section

Platform Selection

HackerOne Format

Markdown sections: Summary, Vulnerability Details, Steps to Reproduce, Impact, Recommended Fix
Include CVSS 3.1 score + vector string
Include two test account setup instructions
Keep under 600 words

Bugcrowd Format

Title with VRT category: [VRT Category] > [Subcategory] > P[1-4]
Expected vs Actual Behavior section
Severity Justification section referencing Bugcrowd VRT

Intigriti Format

CVSS score prominent at top
Clear reproduction steps
Business impact focused

Immunefi Format (Web3)

Root cause in Solidity code
Foundry PoC test included
Economic impact quantified in $ value
Comparison evidence (same check present elsewhere, missing here)

Writing Rules

Never use: "could potentially", "may allow", "might be possible"
Always prove: show actual data/action, not just "200 OK"
Impact first: sentence 1 = what attacker gets, not what the bug is
Quantify: how many users affected, what data type, $ amount
Short: triagers skim. < 600 words.
Human: write to a person, not a system

Read the full file on GitHub · 116 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

4d ago First seen · 116 lines · 0 tokens per session scan A 8dc2ab489c16

Subscribe to this mod's changes

report is a command published in the GitHub repository adriannoes/awesome-agentic-ai (56 stars, last pushed 10d ago), licensed MIT. It adds 52 tokens to every session and 926 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to report, differing in 22 lines, and is treated as a copy.

Security Writing and docs agentic-ai ai ai-agents ai-coding ai-tools awesome-list

report