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dsh-tool-web-enhanced
Advanced tools
Modular search tool for DeepSeek Harness: attach SearXNG, RAG and your own sections to the native web_search.
A drop-in replacement for the stock web_search tool that is modular by sections: the native search results stay as the first section, and you attach additional search modules — each contributing its own section — such as a local SearXNG instance and RAG databases (local markdown sources). The native behaviour is unchanged; everything else is optional.
dsh-tool-web-enhanced is a drop-in replacement for DeepSeek Harness' stock web_search tool. When no modules are configured, web_search behaves exactly like stock: the native results are the only section. Turn on a module and it contributes its own section to the same search response:
SearchSection) plus a config surface (sections:), so adding a new section type is a small, documented, code-level step (fork or PR the repo).Everything is optional: with no modules configured, web_search is exactly stock.
SearchSection registered under sections:. Native results stay first; every additional module renders as its own section.SearXNG results) and a RAG section over local markdown databases (one RAG — <dbName> block per database).topic and sources parameters — topic forwards a vertical hint to modules that support it; sources picks any combination of native / SearXNG / RAG (native, searxng, rag, or all).tool-web row automatically on install.npm install dsh-tool-web-enhanced
This is a DSH bundle: package.json carries dsh.bundle.patch = ./cordis.patch.yml, which inserts the enhanced plugin row and disables the stock tool-web row in one install. Installing the package is the whole swap for CLI profiles — no manual profile edit required. For preset-realm web surfaces, the preset still disables its own tool-web row.
# cordis.patch.yml (bundled with this package)
- insert:
- id: tool-web-enhanced
name: dsh-tool-web-enhanced
config:
search: true
fetch: true
sections:
searxng:
enabled: true
url: 'http://127.0.0.1:8080'
rag:
enabled: true
storePath: ''
embeddings:
provider: auto
apiKeyEnv: EMBEDDING_API_KEY
apiKey: ''
databases: []
- id: tool-web
disabled: true
Installing self-disables the stock tool-web row, so this package is the entire web-search swap.
The enhanced behaviour lives under one unified sections: container. Keys are neutral parameter names. Stock search / fetch keys keep their existing names and defaults.
| Key | Type | Default | Description |
|---|---|---|---|
search | boolean | true | Register web_search. |
fetch | boolean | true | Register web_fetch (unchanged). |
sections.searxng.enabled | boolean | true | Enable the SearXNG section. |
sections.searxng.url | string | http://127.0.0.1:8080 | Base URL of the local SearXNG JSON API. |
sections.rag.enabled | boolean | true | Enable the RAG section + rag_index tool. |
sections.rag.storePath | string | '' (auto) | Search-index store path; empty → a default under the data home. |
sections.rag.embeddings.provider | string | auto | Embedding selection: auto / local / remote. auto → remote when a key is set, else local. |
sections.rag.embeddings.apiKeyEnv | string | EMBEDDING_API_KEY | Env var holding the remote provider's key. |
sections.rag.embeddings.apiKey | string | '' | Literal remote provider key (wins over apiKeyEnv). |
sections.rag.embeddings.model | string | (a multilingual embedding model) | Remote embedding model. |
sections.rag.embeddings.baseURL | string | (your embeddings endpoint) | Remote embeddings API base URL (embeddings-API-compatible). |
sections.rag.embeddings.localModel | string | (a small local embedding model) | Local embedding model (downloaded on first use). |
sections.rag.databases[].name | string | — | Database (section) name. |
sections.rag.databases[].path | string | — | Directory of markdown files to index. |
sections.rag.databases[].topK | number | 5 | Results returned per database. |
The stock search / fetch keys are kept unchanged for drop-in compatibility.
web_search accepts the stock query plus two optional parameters:
| Param | Required | Description |
|---|---|---|
query | yes | The search query. |
topic | no | Vertical hint, forwarded to sections that support it (e.g. SearXNG categories): general, news, science, it, files, social media, images, videos, map, music. |
sources | no | Comma-separated tokens — native plus each enabled section id. Default all. Examples: native,searxng or searxng,rag. |
The output shape carries the native results plus a sections array — one entry per module that returned results:
{
"content": "...", // optional native answer
"sources": [ { "url": "...", "title": "...", "snippet": "..." } ], // native
"truncated": false,
"sections": [
{
"name": "SearXNG results",
"sources": [ { "url": "...", "title": "...", "snippet": "...", "score": 0.9 } ]
},
{
"name": "RAG — my-docs",
"sources": [ { "url": "...", "title": "...", "path": "...", "score": 0.72 } ]
}
]
}
The SearXNG section is optional, and the plugin only talks to a SearXNG instance over its local JSON API (format=json). Point sections.searxng.url at the base URL of any instance that exposes JSON output:
GET {sections.searxng.url}/search?q=<query>&format=json[&categories=<topic>]
The simplest way to stand one up is a Docker Compose service exposing the JSON API on a local port. Having no running instance is fine: the SearXNG section is silently omitted when it is disabled, unreachable, or empty.
Guarantee: when a module is absent, disabled, or unreachable,
web_searchnever errors — the section is simply omitted and results degrade to whatever remains (down to native-only, exactly stock).
The RAG module indexes local markdown databases into an on-machine store and, on every search, retrieves the most similar chunks per database — one RAG — <dbName> section per configured database.
The embedding step is used in two places: to index each chunk, and to embed the query on every search. With the local path (no key configured) indexing and query data stay on the machine; a remote provider is used only if you configure one — nothing is sent unless a provider is configured.
When RAG is enabled with at least one database, a rag_index tool is registered. It rebuilds the local RAG index for all configured databases and returns the number of chunks indexed per database. The index is also built automatically (async, non-blocking) on startup.
The whole point of this package is that web_search is modular by sections. To add a new search source you write a small, self-contained module — no changes to the core tool:
SearchSection — give it an id (used as a sources token), an enabled flag, and a run(query, ctx) method that returns the section's result blocks (SectionBlock[]).sections: in cordis.patch.yml — any parameters the module needs.buildSections — register the new module alongside the built-in ones so it is instantiated when enabled.That's it — roughly fifteen lines. The module contract lives in src/modules.ts (the SearchSection interface and buildSections composition point). Because modules are an isolated list, the package is fork/PR-friendly: a new section type is a small, documented, code-level addition that composes with the native-first output shape and the sources selection.
See Usage above: web_search returns the canonical stock fields (content, sources for native, truncated) plus a sections[] array — one entry per module that returned results, each with a name and its own sources[]. A module with no results is omitted entirely.
npm run build — compiles src/ to lib/ with tsc (NodeNext).
node --test — runs the unit tests in test/ against the built lib/.
Smoke-test in a DSH profile — install the local checkout into an isolated development profile, then inspect the composed configuration:
dsh plugin --profile dev add /path/to/dsh-tool-web-enhanced
dsh --profile dev --dump-config
The dumped tree must show the tool-web-enhanced row plus the disabled tool-web row. Exercise web_search end-to-end in that profile afterward.
MIT
FAQs
Modular search tool for DeepSeek Harness: attach SearXNG, RAG and your own sections to the native web_search.
We found that dsh-tool-web-enhanced demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.

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