searxng-deepdive: Instructions file for Codex

AGENTS.md

searxng-deepdive AGENTS.md is an instructions file for Codex, OpenCode from burakaydinofficial/searxng-deepdive. It costs 2,782 tokens per session, scanned A, original, MIT.

Instructions for AI assistants working on searxng-deepdive, an MCP server that lets language-model agents search the web through a SearXNG search service.

In plain words
What is it for?
Use them when installing, building, testing, probing, or modifying the server and its search tools.
Why use it?
They explain the project's purpose, setup, file layout, and design rules so changes fit the existing codebase and report useful errors.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code; mentions AGENTS.md; mentions Codex.

This is burakaydinofficial/searxng-deepdive's own configuration. It tells Codex and OpenCode how to work on searxng-deepdive itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything searxng-deepdive configures →

Reuse

Borrowing it

Nothing to install: this file belongs to burakaydinofficial/searxng-deepdive. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/burakaydinofficial/searxng-deepdive/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/burakaydinofficial/searxng-deepdive

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 2,782 This file is loaded in full into every session.
When invoked 2,782 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.02782 $0.02782
Opus 5 $0.01391 $0.01391
Sonnet 5 $0.00556 $0.00556
Haiku 4.5 $0.00278 $0.00278

Measured 10d ago against content hash 714d55275eea, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

searxng-deepdive AGENTS.md 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 10d 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.

AGENTS.md · 271 lines

How it starts

The opening of the file, as written. The whole thing — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — guide for AI assistants editing this codebase

If you are an AI agent (Claude Code, Cursor, Cline, Aider, Continue, Codex, …) about to make changes here, read this first. It encodes what humans wish you already knew so we don't repeat the same lessons.

For human-facing docs see README.md. This file is for agent-readable working conventions.


What this project is, in three sentences

searxng-deepdive is an MCP server that wraps a SearXNG instance for LLM agents. It exposes four tools (search, search_on_engines, search_by_category, web_url_read) with schemas and descriptions designed for agent-tool-selection ergonomics, not just API completeness. Its design DNA is: convert every silent-wrong code path into an informatively-wrong one — empty results and wrong-tool calls must always carry a hint specific enough that a retry has a real chance.


Setup

Node ≥20.18.1. From repo root:

npm install
npm run build      # tsc — strict mode, noUnusedLocals/Parameters
npm test           # vitest — should be 100+ tests, ~4s

Live development against a running SearXNG:

SEARXNG_URL=http://127.0.0.1:7979 npm run probe   # exercise the SearxngClient directly
SEARXNG_URL=http://127.0.0.1:7979 npm run dev     # start the MCP stdio server

probe bypasses MCP entirely and prints search results — fastest dev loop when you want to see what SearXNG is actually returning.


File map

src/
├── index.ts          # stdio MCP entrypoint; probes /config at startup
├── searxng.ts        # SearXNG HTTP client (getConfig, search, searchMultiPage)
├── schemas.ts        # Zod schemas for tool inputs (single source of truth
│                     #   for runtime validation + JSON schema sent to MCP)
├── descriptions.ts   # Tool description builders, generated dynamically from
│                     #   the live SearxngConfig at server startup
├── tools.ts          # Tool registration + dispatch; doSearch unifies the
│                     #   three search variants. Exports normalizeName,
│                     #   validateEngineSelection, validateCategorySelection,
│                     #   buildZeroResultHint, trimToCompact for tests.
└── url-reader.ts     # web_url_read implementation: undici fetch +
                      #   content-type-aware conversion (HTML/XML →
                      #   node-html-markdown; JSON → pretty-printed code
                      #   fence; plaintext → passthrough) + extraction
                      #   modes (readHeadings, section, paragraphRange,
                      #   window) + 10 MB stream-cap on the body

tests/
├── normalize-name.test.ts        # case/whitespace normalization
├── validators.test.ts            # engine/category cross-validation w/ hints
├── zero-result-hint.test.ts      # every hint trigger + its inverse
├── trim-to-compact.test.ts       # response trimming
├── descriptions.test.ts          # ANTI-PATTERN regex checks for description copy
├── searxng-client.test.ts        # HTTP client w/ undici MockAgent
└── url-reader.test.ts            # extraction helpers + HTTP integration

scripts/
└── probe.ts          # dev-time SearxngClient exerciser (not in published bundle)

.github/workflows/
├── test.yml          # push/PR/dispatch — Node 20/22/24 × {ubuntu,macos,windows} matrix
└── publish.yml       # tags v*.*.* — verifies version, runs tests, then dual-publishes:
                      #   1. npm tarball with sigstore provenance (npm Trusted Publishing)
                      #   2. registry.modelcontextprotocol.io entry (mcp-publisher OIDC).
                      #   server.json version fields are rewritten from the tag at run
                      #   time so contributors only edit package.json per release.

Read the full file on GitHub · 271 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.

  1. 10d ago First seen · 271 lines · 2,782 tokens per session scan A 714d55275eea

Subscribe to this mod's changes

searxng-deepdive AGENTS.md is an instructions file published in the GitHub repository burakaydinofficial/searxng-deepdive (1 stars, last pushed 4d ago), licensed MIT. It adds 2,782 tokens to every session, about $0.0139 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 2026-08-31.

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