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Wiki Arsenal Agent Skill

Fast PARALLEL wiki lookup engine over wiki/techniques + wiki/payloads + wiki/tools + wiki/cheatsheets for a surface/service/vuln-class. Two modes - quick (one qmd search, cheap, fire constantly) and deep (4 parallel subagents, one per area, merged ready-to-use arsenal card, cached). This is the fast path arsenal that `arsenal` delegates to; the hunt-* skills each inline their own qmd_query and can hand off here for a parallel lookup. Use for "what do I use against <surface>", "arsenal for <X>", "deep/full arsenal", "tool + payload + technique + cheatsheet for <X>", "fast wiki lookup", "parallel wiki search", any "how do I attack/exploit <service|vuln-class>" where you want the documented tooling + payloads before hand-rolling.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
320
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/Encod3d-Sec/TORCH --skill wiki-arsenal

What it tells the agent to use

found in the instruction text
Task spawns other agents

The instruction itself

7 sections, as written by the author

wiki-arsenal

The fast, wiki-first lookup engine for "what do I use against this surface". Runs the four

knowledge areas in parallel so a deep lookup is one wall-clock, not four serial reads. arsenal

delegates here; the hunt-* skills each carry their own wiki-first qmd_query (MCP-independent) and

can hand off here for a fast parallel lookup. Never hand-roll from memory when the wiki has the answer.

Input: a surface, service, or vuln-class (e.g. Jenkins on 8080, SSRF, Kerberoasting).

0. Cache check first (0 tokens on a repeat)

Slug the surface (lowercase, non-alnum -> -). If targets/<active-eng>/arsenal/<slug>.md

exists, read and return it. Do not re-spend. (<active-eng> = the dir named in targets/active.md.)

Mode: quick (DEFAULT - fire it constantly)

One mcp__wiki-search__qmd_query over the whole index (add a qmd_search keyword pass when the

surface is an exact product/CVE string). Group the hits under the four areas and return each as

path -> one-line snippet:

  • Techniques (wiki/techniques/)
  • Payloads (wiki/payloads/)
  • Tools (wiki/tools/)
  • Cheatsheets (wiki/cheatsheets/)

Cost ~1-2k tokens, no subagents. This is what arsenal calls by default and what you fire on

every new surface to raise wiki coverage cheaply. Stop here unless the surface is worth deep prep.

Mode: deep (opt-in - "deep"/"full arsenal", or a whole service/target worth prepping)

Dispatch FOUR parallel subagents in a SINGLE message (Agent tool), one per area, with

model: haiku - each only reads its area and distils a card, which a lightweight model does well

at a fraction of the cost (a full-model fan-out measured ~170k tokens; haiku cuts that hard). Each

is told to search only its area, read the top 2-3 matching pages, and return a compact ready-to-use

card for its area ONLY (nothing else), citing the page paths it used:

| Agent | Searches | Returns |

|---|---|---|

| tools | wiki/tools/ | the automated tool(s) to run + the exact command line |

| payloads | wiki/payloads/ | ready-to-send payloads for the vuln-class |

| techniques | wiki/techniques/ | the attack steps / chain |

| cheatsheets | wiki/cheatsheets/ | quick copy-paste commands |

Each agent scopes its search to its area: pass a path filter to qmd, or query the whole index

and keep only wiki/<area>/ hits, then read those pages. The pages an agent reads stay in that

agent's context and are discarded; you ingest only its card.

Merge the four returned cards into one arsenal card, four labelled sections plus a final

Sources: line listing every page used.

Persist the deep card

Write the merged card to targets/<active-eng>/arsenal/<slug>.md (create the dir on demand) with

frontmatter surface: and generated:. That is the cache step 0 reads next time.

Guardrails (token control)

  • Default is quick (~1-2k tokens). Only go deep on request or for a real service/target.
  • Deep is bounded: exactly 4 agents on model: haiku, each capped to the top 2-3 pages. The cost

is isolated to the subagents; your main context only gains the merged card.

  • The cache prevents re-spend on the same surface.

Hand off

The full class-specific methodology lives in the matching hunt-* skill. After the arsenal card,

hand off to it (e.g. Skill(hunt-ssrf)) for the actual exploitation loop.

How to use it

Copy the folder

Take encod3d-sec/wiki-arsenal from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.