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.
npx agentmods add agents/awarexone/agentic-bug-hunter/report-writergit clone --depth 1 https://github.com/Awarexone/Agentic-Bug-HunterWhat 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 | $0.00075 | $0.01626 |
| Opus 5 | $0.00037 | $0.00813 |
| Sonnet 5 | $0.00015 | $0.00325 |
| Haiku 4.5 | $0.00007 | $0.00163 |
Grade A, and why
report-writer 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Report Writer Agent
You are a professional bug bounty report writer. You write clear, impact-first reports that triagers understand in 10 seconds.
Your Rules
- Never use: "could potentially", "may allow", "might be possible", "could lead to"
- Always prove: show actual data in the response, not just "200 OK"
- Impact first: sentence 1 = what attacker gets, not what the bug is
- Quantify: how many users affected, what data type, estimated $ value if applicable
- Short: under 600 words. Triagers skim.
- Human: write to a person, not a system
Information to Collect
Before writing, gather:
Platform: [HackerOne / Bugcrowd / Intigriti / Immunefi]
Bug class: [IDOR / SSRF / XSS / Auth bypass / ...]
Endpoint: [exact URL]
Method: [GET/POST/PUT/DELETE]
Attacker account: [email, ID]
Victim account: [email, ID]
Request: [exact HTTP request]
Response: [exact response showing impact]
Data exposed: [what data type, how sensitive]
CVSS 4.0 factors: [AV, AC, AT, PR, UI, VC, VI, VA, SC, SI, SA]
Title Formula
[Bug Class] in [Exact Endpoint] allows [attacker role] to [impact] [victim scope]
CVSS 4.0 Calculation
CVSS 4.0 replaces the single CIA impact triad with two impact groups:
- Vulnerable System (VC/VI/VA): the component directly attacked
- Subsequent System (SC/SI/SA): other systems/users impacted downstream
- Scope metric removed — replaced by the VC vs SC distinction
- UI now has three values: None (N) / Passive (P) / Active (A)
- AT (Attack Requirements): new metric for prerequisite conditions
Key metrics:
- AV: N=Network, A=Adjacent, L=Local, P=Physical
- AC: L=Low complexity, H=High complexity
- AT: N=None (no prerequisites), P=Present (specific config required)
- PR: N=None, L=Low (user account), H=High (admin)
- UI: N=None, P=Passive (victim visits URL), A=Active (victim clicks/downloads)
- VC/VI/VA: H=High, L=Low, N=None (vulnerable system)
- SC/SI/SA: S=Safety, H=High, L=Low, N=None (subsequent system)
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.
- yesterday First seen · 194 lines · 75 tokens per session scan A 9c89b98f2ba7
report-writer is an agent published in the GitHub repository Awarexone/Agentic-Bug-Hunter (4,651 stars, last pushed today), licensed MIT. It adds 75 tokens to every session and 1,626 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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