<!-- Generated by scripts/gen-tool-catalog.ts — do not edit by hand.
     Run `pnpm run gen-tool-catalog` to regenerate. -->

# Tool Schema Catalog

Every model-facing tool a shipped plugin contributes to `ctx.tools`: the `name`, `description`, and JSON-Schema `parameters` the model receives via the system-prompt assembly. It complements the cordis [events](cordis-catalog/events.md) & [services](cordis-catalog/services.md) catalogs (the wiring a plugin listens to and calls) and [core-data-structures/](core-data-structures/core.md) (the types those signatures move) — this page is the *tools* the agent is offered.

This file is GENERATED and verified fresh by `pnpm run verify-tool-catalog` (part of `doc-sync`) — do not edit it by hand. Unlike the cordis catalog (a pure source-AST pass), this generator BOOTS each tool plugin on a real context and reads `ctx.tools.schemas()`, because a tool schema is not statically knowable (runtime-spread enums, concatenated descriptions, config-driven names, raw-JSON-Schema MCP tools). A completeness guard globs `packages/*/tool-*` and fails if any package is missing from the generator's boot manifest, so a new tool cannot be silently undocumented. See [the tool-schema-catalog RFC](rfc/implemented/process/2026-07-02-tool-schema-catalog.md).

Scope: shipped product tools under `packages/*/tool-*`, each booted with its DEFAULT config. The registered tool NAME can be a load-time config (e.g. `tool-subagent`'s `toolName`), so a deployment may surface a package under a different or additional name — a per-package note records those shipped aliases where they exist. The `examples/` demo tools (e.g. `echo`) are excluded, matching the cordis catalog's packages-only scope.

## Tool Package Map

This table connects model-visible tool names to the plugin package and service seams behind them. Exact JSON Schemas follow in the package sections below.

| Tool package | Model-visible names | Requires | Writes / affects | Shipped aliases | Deployment note |
| --- | --- | --- | --- | --- | --- |
| `@deepseek-ai/dsh-tool-ask-user` | `ask_user_question` | `ctx.tools`, `ctx.userInteraction` | `tool/call`, `tool/result after a UI/provider answers the question` | - | ask_user_question pauses the tool call until the active UI provider returns a human answer. |
| `@deepseek-ai/dsh-tools` | `run_code` | `ctx.tools`, `ctx.codeRuntime (execution time)`, `ctx.systemPrompt` | `tool/call`, `one tool/code-dispatch per bridged sub-call`, `tool/result` | - | Registered by the tool registry itself under `mode: code` / `mode: both` (see the Code Mode RFC). Under `code` it is the ONLY wire tool; the other registered tools are declared to the model as a generated TypeScript SDK prompt section instead, and a program calls them through port-bridged bindings that dispatch through the ordinary tools/pre-execute → tools/post-execute pipeline, one at a time. |
| `@deepseek-ai/dsh-tool-bash` | `bash`, `bash_kill`, `bash_output` | `ctx.tools`, `ctx.bash` | `tool/call`, `tool/result`, `context/message via agent.inject() for background completion notices` | - | The bash/bash_output/bash_kill tools are model-facing consumers of the bash executor seam. |
| `@deepseek-ai/dsh-tool-cordis` | `cordis_inspect`, `cordis_mount`, `cordis_unmount` | `ctx.tools` | `tool/call`, `tool/result`, `live plugin-tree mutations (mount/unmount)` | - | Ships in examples/cordis-agent only (a deliberate opt-in — mounted code gets the real ctx, see docs/rfc/implemented/feature/2026-07-08-self-referential-cordis-toolset.md). Plugins the model mounts may register ADDITIONAL model-visible tools at runtime; the request-header ToolsDelta logs those tool-set changes. |
| `@deepseek-ai/dsh-tool-fs` | `edit`, `read`, `write` | `ctx.tools`, `ctx.fs`, `ctx.systemPrompt` | `tool/call`, `fs/write-intent or fs/edit-intent for mutations`, `fs/observed after successful file operations`, `tool/result` | - | The read-before-write/edit policy is added by `@deepseek-ai/dsh-fs-policy` (an `fs/*` event-gate plugin, no schema change); a deployment that loads these tools is expected to also load it. The tool schemas above are identical with or without the policy plugin. |
| `@deepseek-ai/dsh-tool-skill` | `skill` | `ctx.tools`, `ctx.skills` | `tool/call`, `tool/result` | - | - |
| `@deepseek-ai/dsh-tool-subagent` | `subagent` | `ctx.tools`, `ctx.subagents` | `tool/call`, `tool/result`, `child session events through the chosen provider` | `subagent`, `subagent_fork` | The registered tool name is the load-time `toolName` config (default `subagent`); the schema above is that default. The shipped example agents load this package once per subagent backend, so the model additionally sees `subagent_fork` (bound to the fork backend) with an identical schema — see `examples/coding-agent/cordis.yml` and `examples/acp-agent/cordis.yml`. |
| `@deepseek-ai/dsh-tool-todo` | `todo_write` | `ctx.tools`, `owning Agent session` | `tool/call`, `todo/write`, `tool/result` | - | todo_write is session-owned state; UIs render the latest todo/write event as a checklist or ACP plan. |
| `@deepseek-ai/dsh-tool-workflow` | `workflow` | `ctx.tools`, `ctx.workflows`, `ctx.systemPrompt`, `a calling Agent (exec.agent parents the script children)` | `tool/call`, `tool/result` | - | - |
| `@deepseek-ai/dsh-tool-web` | `web_fetch`, `web_search` | `ctx.tools`, `ctx.web`, `ctx.systemPrompt` | `tool/call`, `tool/result` | - | web_search and web_fetch keep provider selection behind ctx.web so model-visible schemas stay stable across backend swaps. |

## `@deepseek-ai/dsh-tool-ask-user`

### `ask_user_question`

Ask the user a concise question when you need confirmation, a choice, or missing information before proceeding. Send one or more questions, each with a stable id that will be echoed in the answer.

```json
{
  "type": "object",
  "properties": {
    "questions": {
      "type": "array",
      "description": "Questions to ask the user before continuing.",
      "items": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Stable id for this question; echoed in the answer."
          },
          "question": {
            "type": "string",
            "description": "The specific question to ask the user."
          },
          "header": {
            "type": "string",
            "description": "Optional short heading for the question, such as \"Confirm\" or \"Choose Mode\"."
          },
          "options": {
            "type": "array",
            "description": "Optional choices to show the user. If you recommend one, put it first and append \"(Recommended)\" to that label.",
            "items": {
              "type": "object",
              "properties": {
                "label": {
                  "type": "string",
                  "description": "Short user-facing option label."
                },
                "description": {
                  "type": "string",
                  "description": "One sentence explaining the tradeoff or impact."
                }
              },
              "required": [
                "label"
              ]
            }
          },
          "multi_select": {
            "type": "boolean",
            "description": "Whether the user may select more than one option. Defaults to false."
          }
        },
        "required": [
          "id",
          "question"
        ]
      }
    }
  },
  "required": [
    "questions"
  ]
}
```

Source: [`packages/ui/tool-ask-user/src/index.ts`](../packages/ui/tool-ask-user/src/index.ts)

ask_user_question pauses the tool call until the active UI provider returns a human answer.

## `@deepseek-ai/dsh-tools`

### `run_code`

Execute a TypeScript program against the available tools. Write the BODY of an async function (erasable syntax only; top-level `await` and `return` work) and call tools as `await tools.name(args)` per the declarations in the system prompt. Only what you print or return comes back — curate it.

```json
{
  "type": "object",
  "properties": {
    "code": {
      "type": "string",
      "description": "The program: the body of an async TypeScript function."
    }
  },
  "required": [
    "code"
  ]
}
```

Source: [`packages/core/tools/src/code-mode.ts`](../packages/core/tools/src/code-mode.ts)

Registered by the tool registry itself under `mode: code` / `mode: both` (see the Code Mode RFC). Under `code` it is the ONLY wire tool; the other registered tools are declared to the model as a generated TypeScript SDK prompt section instead, and a program calls them through port-bridged bindings that dispatch through the ordinary tools/pre-execute → tools/post-execute pipeline, one at a time.

## `@deepseek-ai/dsh-tool-bash`

### `bash`

Execute a bash command (`bash -c`) and return its stdout/stderr. Each call runs in a fresh shell: no state (cwd, variables, functions) persists between calls — pass `workdir` instead of using `cd`. Non-zero exits are reported as `[exit code: N]`. Commands may run under a file sandbox; a blocked file operation is reported as `[sandbox: file access denied under <mode> mode]` — a policy denial, not a bug in the command; do not retry another way (a background task reports the same marker via bash_output once it has finished). Long output is truncated to its tail; the full output is saved to a file whose path is reported when available. Set `run_in_background: true` for long-running commands: the call returns a task id immediately; poll it with `bash_output` and stop it with `bash_kill`.

```json
{
  "type": "object",
  "properties": {
    "command": {
      "type": "string",
      "description": "The bash command to execute."
    },
    "description": {
      "type": "string",
      "description": "Clear, concise description of what this command does in active voice, 5-10 words (shown in the UI). Examples: \"ls\" → \"List files in current directory\"; \"git status\" → \"Show working tree status\"; \"npm install\" → \"Install package dependencies\"."
    },
    "timeoutMs": {
      "type": "number",
      "description": "Timeout in milliseconds. The executor applies its configured default and cap, and kills the command on expiry."
    },
    "workdir": {
      "type": "string",
      "description": "Working directory for this command. Defaults to the session workspace; a relative path is resolved against it."
    },
    "run_in_background": {
      "type": "boolean",
      "description": "Run in the background and return a task id immediately. No timeout applies."
    }
  },
  "required": [
    "command",
    "description"
  ]
}
```

Source: [`packages/bash/tool-bash/src/index.ts`](../packages/bash/tool-bash/src/index.ts)

### `bash_kill`

Ask the executor to kill a running background bash task by task id.

```json
{
  "type": "object",
  "properties": {
    "task_id": {
      "type": "string",
      "description": "Task id returned by the bash tool."
    }
  },
  "required": [
    "task_id"
  ]
}
```

Source: [`packages/bash/tool-bash/src/index.ts`](../packages/bash/tool-bash/src/index.ts)

### `bash_output`

Read new output from a background bash task started with `bash` + `run_in_background`. Returns only output produced since the previous bash_output call, plus the task status. Tasks keep running while you do other work; poll again later for more output.

```json
{
  "type": "object",
  "properties": {
    "task_id": {
      "type": "string",
      "description": "Task id returned by the bash tool."
    }
  },
  "required": [
    "task_id"
  ]
}
```

Source: [`packages/bash/tool-bash/src/index.ts`](../packages/bash/tool-bash/src/index.ts)

The bash/bash_output/bash_kill tools are model-facing consumers of the bash executor seam.

## `@deepseek-ai/dsh-tool-cordis`

### `cordis_inspect`

Inspect the live cordis runtime that is running THIS agent. Read-only. Sections: `services` (every provided ctx service and the plugin fiber that owns it), `plugins` (a flat list of the loaded plugins with their lifecycle states), `tools` (the model-facing tools currently registered, i.e. what you can call), `dynamic` (plugins you mounted via cordis_mount: id, name, state, provided services, awaited services), `api` (method signatures AND argument/return type shapes for every LIVE service — read this before writing plugin code that calls a service), `events` (every harness event with its dispatch mode and exact signature — pick listener targets here). Omit `what` to get all six sections.

```json
{
  "type": "object",
  "properties": {
    "what": {
      "type": "string",
      "description": "Limit the report to one section. Omit for all sections.",
      "enum": [
        "services",
        "plugins",
        "tools",
        "dynamic",
        "api",
        "events"
      ]
    }
  }
}
```

Source: [`packages/cordis/tool-cordis/src/index.ts`](../packages/cordis/tool-cordis/src/index.ts)

### `cordis_mount`

Mount a NEW cordis plugin into the live runtime that is running THIS agent (self-modification). `code` runs as the body of an async JavaScript function in an isolated sandbox and MUST `return` a plugin. Two forms: FUNCTION form `return (ctx) => { … }` — declares no inject, so it can register tools, listen to events, and provide services, but reaching ANY service (e.g. ctx.bash) throws; use it only when you need no services. OBJECT form `return { name?, inject: ['bash', 'llm', …], apply(ctx) { … } }` — declares dependencies, and cordis activates the plugin only after the services exist; PREFER this form. You may reach ONLY the services you list in inject: an undeclared service throws even if it exists, because an undeclared dependency would not be cleaned up if its provider is unmounted. BEFORE calling a service from your code, read cordis_inspect what:"api" — it lists method signatures AND the type shapes of their arguments/returns (do not guess a field's type; e.g. a bash run's stdout is an object, not a string). Inside `apply`, use the standard cordis API: `ctx.on(event, listener)` to observe events (see cordis_inspect what:"events"), or call `harness.registerTool(ctx, harness.defineTool({ name, description, parameters: { text: { type: 'string', required: true } }, async execute(args) { … } }))` to give yourself a new tool — it becomes callable on your NEXT step. Tool parameters: each key IS a property — { type: 'string'|'number'|'boolean'|'object'|'array', required?: true, description?, enum?, items?, properties? }; a JSON-Schema-style { type: 'object', properties, required: […] } wrapper and type 'integer' are also accepted and normalized. A tool's `execute` MUST return an ARRAY of content blocks, e.g. `return [{ type: 'text', text: someString }]` — never a bare string. Mounts can COMPOSE: one plugin may `ctx.provide('name', value)` a service and another may declare `inject: ['name']` to consume it — the consumer stays pending until the provider exists and returns to pending when the provider is unmounted. Everything registered inside `apply` is cleaned up automatically on unmount. Sandbox globals: `console` (tagged `[cordis:<id>]`, writes through to the harness terminal), `harness.defineTool`, `harness.registerTool`, `btoa`, `atob`, `TextEncoder`, `TextDecoder`. Node APIs are DISABLED — do filesystem/network/timer work through the cordis services, never Node built-ins: `require`, `setTimeout`/`setInterval`, and `fetch` throw redirect errors; `process` and `Buffer` are undefined. Instead use inject: ['fs'] + ctx.fs for files, inject: ['web'] + ctx.web for HTTP, inject: ['bash'] + ctx.bash for processes, and inject: ['timer'] + ctx.setTimeout/ctx.setInterval for timing (fiber effects, auto-cleaned on unmount) — cordis_inspect what:"api" shows what THIS runtime provides. Write PLAIN JavaScript, not TypeScript (no `as`, no type annotations). Cautions: (1) waterfall events (e.g. tools/pre-execute) hand the listener a trailing `next` callback which MUST be called — returning without `next()` VETOES the call; prefer plain notification events unless you intend to intercept. (2) Never await something that only resolves after the current turn (your code runs INSIDE a tool call of that turn — it would deadlock). (3) Your `ctx` is a restricted façade: you can register tools, observe events, provide/consume services, and use timers, but framework internals (ctx.root, ctx.fiber, ctx.extend, ctx.plugin, …) are withheld. It is not a security boundary though — the services you inject (e.g. ctx.bash) reach the real runtime.

```json
{
  "type": "object",
  "properties": {
    "code": {
      "type": "string",
      "description": "Body of an async JS function; must `return` the plugin to mount."
    }
  },
  "required": [
    "code"
  ]
}
```

Source: [`packages/cordis/tool-cordis/src/index.ts`](../packages/cordis/tool-cordis/src/index.ts)

### `cordis_unmount`

Dispose a plugin previously mounted with cordis_mount, by id. All its registrations (event listeners, tools, services) are cleaned up through the cordis effect lifecycle. Returns only after disposal has fully completed (quiescence, not just a request to stop).

```json
{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "The dynamic mount id returned by cordis_mount (e.g. \"dyn-1\")."
    }
  },
  "required": [
    "id"
  ]
}
```

Source: [`packages/cordis/tool-cordis/src/index.ts`](../packages/cordis/tool-cordis/src/index.ts)

Ships in examples/cordis-agent only (a deliberate opt-in — mounted code gets the real ctx, see docs/rfc/implemented/feature/2026-07-08-self-referential-cordis-toolset.md). Plugins the model mounts may register ADDITIONAL model-visible tools at runtime; the request-header ToolsDelta logs those tool-set changes.

## `@deepseek-ai/dsh-tool-fs`

### `edit`

Edit an existing UTF-8 text file by replacing literal text.

```json
{
  "type": "object",
  "properties": {
    "file_path": {
      "type": "string",
      "description": "Path to edit, resolved by the filesystem backend."
    },
    "old_string": {
      "type": "string",
      "description": "Literal text to replace. Must match exactly."
    },
    "new_string": {
      "type": "string",
      "description": "Literal replacement text. Use an empty string to delete the match."
    },
    "replace_all": {
      "type": "boolean",
      "description": "Replace all matches. Defaults to false; when false, old_string must appear exactly once."
    }
  },
  "required": [
    "file_path",
    "old_string",
    "new_string"
  ]
}
```

Source: [`packages/fs/tool-fs/src/index.ts`](../packages/fs/tool-fs/src/index.ts)

### `read`

Read a UTF-8 text file and return line-numbered content.

```json
{
  "type": "object",
  "properties": {
    "file_path": {
      "type": "string",
      "description": "Path to read, resolved by the filesystem backend."
    },
    "offset": {
      "type": "number",
      "description": "1-based first line to return. Defaults to 1."
    },
    "limit": {
      "type": "number",
      "description": "Maximum number of lines to return. Defaults to 2000."
    }
  },
  "required": [
    "file_path"
  ]
}
```

Source: [`packages/fs/tool-fs/src/index.ts`](../packages/fs/tool-fs/src/index.ts)

### `write`

Create or fully replace a UTF-8 text file.

```json
{
  "type": "object",
  "properties": {
    "file_path": {
      "type": "string",
      "description": "Path to write, resolved by the filesystem backend."
    },
    "content": {
      "type": "string",
      "description": "Full UTF-8 text content to write."
    }
  },
  "required": [
    "file_path",
    "content"
  ]
}
```

Source: [`packages/fs/tool-fs/src/index.ts`](../packages/fs/tool-fs/src/index.ts)

The read-before-write/edit policy is added by `@deepseek-ai/dsh-fs-policy` (an `fs/*` event-gate plugin, no schema change); a deployment that loads these tools is expected to also load it. The tool schemas above are identical with or without the policy plugin.

## `@deepseek-ai/dsh-tool-skill`

### `skill`

Load the full instructions for an available skill. Call this with the exact skill name from the session skill catalog before acting on a task that names or clearly matches that skill.

```json
{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "The exact skill name from the available skills list."
    }
  },
  "required": [
    "name"
  ]
}
```

Source: [`packages/skill/tool-skill/src/index.ts`](../packages/skill/tool-skill/src/index.ts)

## `@deepseek-ai/dsh-tool-subagent`

### `subagent`

Delegate a self-contained task to a subagent (a separate agent that works in its own context) and return its final result. Use this to offload focused, independent work — research, a scoped implementation, an analysis — so it does not consume this conversation's context. The subagent runs to completion and you receive only its final answer, not its intermediate steps. Give it a complete, standalone prompt: it does not see this conversation.

```json
{
  "type": "object",
  "properties": {
    "description": {
      "type": "string",
      "description": "A short (3-5 word) description of the delegated task, for display."
    },
    "prompt": {
      "type": "string",
      "description": "The complete, self-contained task for the subagent. It does not share this conversation's context, so include everything it needs."
    }
  },
  "required": [
    "description",
    "prompt"
  ]
}
```

Source: [`packages/subagent/tool-subagent/src/index.ts`](../packages/subagent/tool-subagent/src/index.ts)

The registered tool name is the load-time `toolName` config (default `subagent`); the schema above is that default. The shipped example agents load this package once per subagent backend, so the model additionally sees `subagent_fork` (bound to the fork backend) with an identical schema — see `examples/coding-agent/cordis.yml` and `examples/acp-agent/cordis.yml`.

## `@deepseek-ai/dsh-tool-todo`

### `todo_write`

Record and update a structured task list for the current work. Send the ENTIRE list every call — it REPLACES the previous list (there are no partial updates, no per-item edits). Use it to plan multi-step work and show progress: add one todo per concrete step before you start. Keep AT MOST ONE todo `in_progress` at a time; while work remains, exactly one active task should be `in_progress`. Mark a todo `completed` the moment it is done (do not batch completions), and allow no `in_progress` item only once all work is complete. Skip the list for trivial single-step tasks. Statuses: `pending` (not started), `in_progress` (being worked on now), `completed` (finished).

```json
{
  "type": "object",
  "properties": {
    "todos": {
      "type": "array",
      "description": "The COMPLETE task list, replacing any previous list.",
      "items": {
        "type": "object",
        "properties": {
          "content": {
            "type": "string",
            "description": "What the task is — a short imperative line."
          },
          "status": {
            "type": "string",
            "description": "pending (not started) | in_progress (now) | completed (done).",
            "enum": [
              "pending",
              "in_progress",
              "completed"
            ]
          }
        },
        "required": [
          "content",
          "status"
        ]
      }
    }
  },
  "required": [
    "todos"
  ]
}
```

Source: [`packages/todo/tool-todo/src/index.ts`](../packages/todo/tool-todo/src/index.ts)

todo_write is session-owned state; UIs render the latest todo/write event as a checklist or ACP plan.

## `@deepseek-ai/dsh-tool-workflow`

### `workflow`

Run a JavaScript workflow script that orchestrates subagents at scale. Use this for work that fans out across many independent pieces — an audit over many files, a migration, multi-angle research, adversarial verification of findings — where you write the orchestration as a script instead of delegating turn by turn.

The workflow's identity rides the `meta` parameter as JSON: required `name` (short kebab-case) and `description` strings, optional `whenToUse` string and `phases` array (`{title, detail?, model?}`). The `script` parameter is the plain JavaScript body ONLY (NOT TypeScript, and NO `export const meta` statement — meta is a parameter, not code), running with top-level await; end with `return <value>` — the value must be JSON-serializable and is this tool's result.

Script-body hooks:
- `agent(prompt, opts?): Promise<any>` — run one subagent to completion. Without `opts.schema` it resolves to the child's final text; with `opts.schema` (an object-rooted JSON Schema using ONLY type/properties/required/additionalProperties/items/enum/const — no oneOf/pattern/format/numeric bounds) it resolves to the validated object. Resolves `null` when the child fails (filter with `.filter(Boolean)`). Other opts: `label` (display), `phase` (progress group), `model` (override). Anything else (`effort`/`isolation`/`agentType`) is rejected loudly.
- `pipeline(items, ...stages): Promise<any[]>` — run each item through the stages independently with NO barrier between stages (prefer this for multi-stage work). Each stage receives `(prev, item, index)`. An ordinary stage throw drops that ITEM to `null` and skips its remaining stages.
- `parallel(thunks): Promise<any[]>` — run zero-argument functions concurrently and await ALL of them (a barrier; use only when a stage genuinely needs every prior result together). A throwing thunk resolves to `null`.
- `phase(title)` — start a progress phase; `log(message)` — narrate progress; `args` — the tool call's `args` input, verbatim.

Misused hooks (bad arguments, unknown options, unsupported schemas, tripped caps) throw errors that ALWAYS kill the script — they never dissolve into a per-item `null`.

Constraints: concurrency and total-agent caps apply; no filesystem, network, timers, or Node.js APIs are provided — the agents do the work, the script only coordinates them. The run executes in the foreground: this call returns when the whole script finishes.

```json
{
  "type": "object",
  "properties": {
    "script": {
      "type": "string",
      "description": "The plain-JS workflow script body (top-level await allowed; NO `export const meta` statement; end with `return <json-value>`)."
    },
    "meta": {
      "type": "object",
      "description": "The workflow identity block (plain JSON — never code).",
      "properties": {
        "name": {
          "type": "string",
          "description": "Short kebab-case workflow name."
        },
        "description": {
          "type": "string",
          "description": "One-line description of what the workflow does."
        },
        "whenToUse": {
          "type": "string",
          "description": "Optional guidance on when this workflow applies."
        },
        "phases": {
          "type": "array",
          "description": "Optional phase declarations matched by phase() calls.",
          "items": {
            "type": "object",
            "properties": {
              "title": {
                "type": "string",
                "description": "The phase title phase() calls match by exact string."
              },
              "detail": {
                "type": "string",
                "description": "Optional one-line description of the phase."
              },
              "model": {
                "type": "string",
                "description": "Optional model override this phase is expected to use."
              }
            },
            "required": [
              "title"
            ]
          }
        }
      },
      "required": [
        "name",
        "description"
      ]
    },
    "args": {
      "type": "object",
      "description": "Optional JSON input exposed to the script as the `args` global (wrap a bare list as a field, e.g. {\"files\": [...]})."
    }
  },
  "required": [
    "script",
    "meta"
  ]
}
```

Source: [`packages/workflow/tool-workflow/src/index.ts`](../packages/workflow/tool-workflow/src/index.ts)

## `@deepseek-ai/dsh-tool-web`

### `web_fetch`

Fetch the content of a specific HTTP(S) URL and return it decoded to text.

```json
{
  "type": "object",
  "properties": {
    "url": {
      "type": "string",
      "description": "The HTTP(S) URL to fetch."
    }
  },
  "required": [
    "url"
  ]
}
```

Source: [`packages/web/tool-web/src/index.ts`](../packages/web/tool-web/src/index.ts)

### `web_search`

Search the web for current information. Returns an optional summary answer and a list of source URLs.

```json
{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "The search query."
    }
  },
  "required": [
    "query"
  ]
}
```

Source: [`packages/web/tool-web/src/index.ts`](../packages/web/tool-web/src/index.ts)

web_search and web_fetch keep provider selection behind ctx.web so model-visible schemas stay stable across backend swaps.
