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 skills add 0dayInc/pwn --skill combo_nationgit clone --depth 1 https://github.com/0dayInc/pwnWrote 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/0dayinc/pwn/combo_nation)<a href="https://agentmods.dev/skills/0dayinc/pwn/combo_nation"><img src="https://agentmods.dev/badge/skills/0dayinc/pwn/combo_nation/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/0dayinc/pwn/combo_nation"><img src="https://agentmods.dev/badge/skills/0dayinc/pwn/combo_nation.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 | $0.00025 | $0.00416 |
| Opus 5 | $0.00013 | $0.00208 |
| Sonnet 5 | $0.00005 | $0.00083 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
pwn-ai-mcp-combonation 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 today.
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.
What it actually says
PWN::AI::MCP::ComboNation
JSON-RPC 2.0 / MCP 2024-11-05 stdio client for combo.nation. Speaks the native menu-oriented tools over newline-delimited JSON; it does not scrape a terminal or enable hardware unless requested.
When to use
Call PWN::AI::MCP::ComboNation from pwn_eval when the task needs this module.
Do not reimplement it in shell.
Methodologies
Generated from pwn/ai/mcp/combo_nation.rb. Prefer the public class methods below.
Class methods take (opts = {}) and read opts.
How to call
PWN::AI::MCP::ComboNation.help
PWN::AI::MCP::ComboNation.required_bins(opts)
Public methods
required_binsargvconnectdisconnectrequestnotifypinglist_toolscall_toolmenu_catalogmenu_mainmenu_dial_calibrationmenu_guesshardware_connectoperation_statusoperation_answeroperation_cancelservo_pausepoll_untilauthorshelp
Source
pwn/ai/mcp/combo_nation.rb
Verification
PWN::AI::MCP::ComboNation.respond_to?(:required_bins) after the
module is loaded. Read the source for parameter names.
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.
- today First seen · 66 lines · 25 tokens per session scan A 8425f06189bc
pwn-ai-mcp-combonation is a skill published in the GitHub repository 0dayInc/pwn (82 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 416 once invoked, about $0.0001 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 2026-09-11.
Other skills, from other repositories
analyzing-linux-elf-malware
Analyze malicious Linux ELF binaries — botnets, cryptominers, ransomware, and rootkits targeting Linux servers, containers, and cloud infrastructure — through static analysis, dynamic tracing, and reverse engineering of x8664 and ARM samples. Use when investigating Linux malware, triaging a suspicious ELF binary…
osmedeus-expert
Expert guide for the Osmedeus security automation workflow engine. Use when: (1) writing or editing YAML workflows (modules and flows), (2) running osmedeus CLI commands (scan, workflow management, installation, server), (3) configuring steps, runners, triggers, or template variables, (4) debugging workflow execution…
performing-jwt-none-algorithm-attack
Execute and test the JWT none algorithm attack to bypass signature verification by manipulating the alg header field in JSON Web Tokens.
supabase
Supabase / PostgREST Row-Level-Security playbook — pull the anon (or leaked servicerole) key out of the frontend JS, map tables from the auto-generated OpenAPI spec, test anonymous RLS READ disclosures (PII/secret leaks), and anonymous RLS WRITE abuse (insert/update/delete — e.g. forging…
performing-ai-assisted-vulnerability-discovery
Using LLMs to accelerate vulnerability research and pentest workflows — generating syntax-valid fuzzing seeds and evolving grammars, fine-tuned mutation dictionaries, parallel agent-based proof-of-vulnerability generation, and evidence-driven passive analysis of real HTTP traffic via the Burp MCP server. Covers…
graphql
GraphQL pentest playbook — find the endpoint, dump the schema (introspection or field-suggestion fallback), then test for authorization gaps, query batching, alias overload, depth-based DoS, and SQLi/NoSQLi in resolver arguments. Use when the target exposes a /graphql endpoint, GraphiQL, Apollo, or accepts GraphQL…