Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/akashrpatil/awesome-offensive-security-skillsnpx agentmods add skills/akashrpatil/awesome-offensive-security-skills/bug-bounty-workflow-funnelWrote 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.
[](https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/bug-bounty-workflow-funnel)<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/bug-bounty-workflow-funnel"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/bug-bounty-workflow-funnel/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/bug-bounty-workflow-funnel"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/bug-bounty-workflow-funnel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00046 | $0.02464 |
| Opus 5 | $0.00023 | $0.01232 |
| Sonnet 5 | $0.00009 | $0.00493 |
| Haiku 4.5 | $0.00005 | $0.00246 |
Grade A, and why
bug-bounty-workflow-funnel scanned grade A with 1 finding 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
[Exact curl command / Burp request / script that reproduces the bug] This is a copy
100% identical to bug-bounty-workflow-funnel — 0 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.
How it starts
The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug Bounty Workflow Funnel
When to Use
- When starting a new bug bounty program and need a structured data management system.
- When drowning in raw notes and need to triage observations into actionable items.
- When preparing to convert confirmed bugs into polished submission reports.
- When working in a team and need a shared vocabulary for finding severity stages.
Prerequisites
- A target program with defined scope (HackerOne / Bugcrowd / Intigriti / VDP)
- A note-taking system (Obsidian, Notion, plain Markdown files, or similar)
- Claude Code CLI for AI-assisted triage and report generation (optional but recommended)
Core Concept: The 5-Stage Funnel
"Structure your hacking data like a sales funnel. Raw observations at the top, polished reports at the bottom." — Critical Thinking Podcast, Ep. 166 [37:42]
flowchart TB
N["📝 NOTES<br/>(All raw observations)"]
L["🔍 LEADS<br/>(Interesting patterns)"]
P["🔧 PRIMITIVES / GADGETS<br/>(Reusable techniques & entry points)"]
F["🐛 FINDINGS<br/>(Confirmed vulnerabilities)"]
R["📄 REPORTS<br/>(Submission-ready documentation)"]
N --> L --> P --> F --> R
style N fill:#1a1a2e,stroke:#e94560,color:#fff
style L fill:#1a1a2e,stroke:#f9a826,color:#fff
style P fill:#1a1a2e,stroke:#16c79a,color:#fff
style F fill:#1a1a2e,stroke:#11999e,color:#fff
style R fill:#1a1a2e,stroke:#6c5ce7,color:#fff
Workflow
Stage 1: Notes (Raw Observations)
Everything goes here. No filtering. No judgment. Write it down NOW, evaluate LATER.
Directory structure:
target-name/
├── notes/
│ ├── 2025-01-15-initial-recon.md
│ ├── 2025-01-15-auth-flow-analysis.md
│ ├── 2025-01-16-api-endpoint-mapping.md
│ └── 2025-01-16-js-source-review.md
Note template:
# [Date] [Topic]
## Context
- Target: [subdomain/endpoint/feature]
- Tool used: [Burp/Browser DevTools/ffuf/etc]
- Time spent: [duration]
## Observations
- [Observation 1]
- [Observation 2]
## Raw Data
[Paste interesting requests/responses/code snippets here]
## Gut Feeling
- [ ] Worth investigating further
- [ ] Dead end
- [ ] Need more context
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.
- 8d ago First seen · 286 lines · 46 tokens per session scan A f9977dba362e
bug-bounty-workflow-funnel is a skill published in the GitHub repository akashrpatil/awesome-offensive-security-skills (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 46 tokens to every session and 2,464 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to bug-bounty-workflow-funnel, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
bug-bounty-workflow-funnel
Implement the 5-stage Funnel workflow (Notes → Leads → Primitives → Findings → Reports) for structured bug bounty hunting. Based on Critical Thinking Bug Bounty Podcast Episode 166.
contradiction-analysis
A structured way to analyze difficult problems by identifying competing forces, finding the main conflict, and deciding which side or issue has the greatest effect.
criticism-self-criticism
A structured review method for examining completed work, criticism, and repeated mistakes. It focuses on specific evidence, causes, effects, and practical improvements.
investigation-first
A research-first method for making decisions when the available facts, context, or first-hand evidence are incomplete.
mass-line
A method for collecting feedback and facts from multiple people or sources, turning them into a plan, and checking the plan with those affected.
practice-cognition
A method for testing ideas in practice, learning from the results, and improving the next attempt through repeated cycles.