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get_deleted_posts

Retrieve deleted posts from Gelbooru by specifying a starting post ID to fetch content removed above that threshold.

Instructions

Retrieve deleted posts. Pass last_id to get everything deleted above that post ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
last_idNoReturn deleted posts whose ID is above this value.
limitNo

Implementation Reference

  • Handler implementation for get_deleted_posts - constructs API parameters with deleted='show' and optional last_id/limit filters, then calls the _get helper to fetch results from Gelbooru API.
    elif name == "get_deleted_posts":
        params = {"page": "dapi", "s": "post", "q": "index", "deleted": "show"}
        if "last_id" in arguments:
            params["last_id"] = arguments["last_id"]
        if "limit" in arguments:
            params["limit"] = arguments["limit"]
        result = await loop.run_in_executor(None, _get, params)
  • Tool registration with schema definition for get_deleted_posts - defines input parameters (last_id, limit) and their validation rules.
    Tool(
        name="get_deleted_posts",
        description=(
            "Retrieve deleted posts. Pass last_id to get everything deleted "
            "above that post ID."
        ),
        inputSchema={
            "type": "object",
            "properties": {
                "last_id": {
                    "type": "integer",
                    "description": "Return deleted posts whose ID is above this value.",
                },
                "limit": {"type": "integer", "default": 20, "minimum": 1, "maximum": 100},
            },
        },
    ),
  • Helper function _get that performs HTTP GET requests to the Gelbooru API, handles authentication, JSON parsing, and error handling. Used by get_deleted_posts to fetch data.
    def _get(params: dict) -> Any:
        """Perform a synchronous HTTP GET and return parsed JSON."""
        params = {**params, "json": "1"}   # copy — never mutate the caller's dict
        _build_auth(params)
        url = f"{BASE_URL}?{urlencode(params)}"
        req = Request(url, headers={"User-Agent": "GelbooruMCP/1.0"})
        try:
            with urlopen(req, timeout=15) as resp:
                raw = resp.read().decode("utf-8")
        except URLError as exc:
            return {"error": str(exc)}
        try:
            return json.loads(raw)
        except json.JSONDecodeError:
            # Some endpoints return XML/empty on error; surface the raw text
            return {"raw": raw}
  • MCP server list_tools handler that registers all available tools including get_deleted_posts, making it discoverable to clients.
    @server.list_tools()
    async def list_tools() -> list[Tool]:
        return [
            Tool(
                name="search_posts",
                description=(
                    "Search Gelbooru posts by tags, page, limit, or ID. "
                    "Supports all Gelbooru tag syntax: AND (tag1 tag2), OR ({t1~t2}), "
                    "NOT (-tag), wildcards (*tag / tag*), meta-tags like "
                    "rating:safe/questionable/explicit, score:>=N, width:>=N, "
                    "user:name, sort:random, sort:score:desc, etc."
                ),
                inputSchema={
                    "type": "object",
                    "properties": {
                        "tags": {
                            "type": "string",
                            "description": (
                                "Tag query string. Examples: 'cat_ears blue_eyes', "
                                "'touhou -rating:explicit', 'score:>=50 sort:score:desc'"
                            ),
                        },
                        "limit": {
                            "type": "integer",
                            "description": "Number of posts to return (default 20, max 100).",
                            "default": 20,
                            "minimum": 1,
                            "maximum": 100,
                        },
                        "pid": {
                            "type": "integer",
                            "description": "Page number (0-indexed).",
                            "default": 0,
                        },
                        "id": {
                            "type": "integer",
                            "description": "Fetch a single post by its Gelbooru ID.",
                        },
                        "cid": {
                            "type": "integer",
                            "description": "Fetch posts by change ID (Unix timestamp).",
                        },
                    },
                },
            ),
            Tool(
                name="get_deleted_posts",
                description=(
                    "Retrieve deleted posts. Pass last_id to get everything deleted "
                    "above that post ID."
                ),
                inputSchema={
                    "type": "object",
                    "properties": {
                        "last_id": {
                            "type": "integer",
                            "description": "Return deleted posts whose ID is above this value.",
                        },
                        "limit": {"type": "integer", "default": 20, "minimum": 1, "maximum": 100},
                    },
                },
            ),
            Tool(
                name="search_tags",
                description=(
                    "Search Gelbooru tags by name, pattern, or ID. "
                    "Useful for autocomplete, tag counts, and tag type lookup."
                ),
                inputSchema={
                    "type": "object",
                    "properties": {
                        "name": {
                            "type": "string",
                            "description": "Exact tag name to look up.",
                        },
                        "names": {
                            "type": "string",
                            "description": "Space-separated list of tag names, e.g. 'cat dog fox'.",
                        },
                        "name_pattern": {
                            "type": "string",
                            "description": (
                                "Wildcard tag search using SQL LIKE syntax. "
                                "Use % for multi-char wildcard, _ for single-char. "
                                "Example: '%choolgirl%'"
                            ),
                        },
                        "id": {
                            "type": "integer",
                            "description": "Look up a tag by its database ID.",
                        },
                        "after_id": {
                            "type": "integer",
                            "description": "Return tags whose ID is greater than this value.",
                        },
                        "limit": {"type": "integer", "default": 20, "minimum": 1, "maximum": 100},
                        "order": {
                            "type": "string",
                            "enum": ["ASC", "DESC"],
                            "description": "Sort direction.",
                        },
                        "orderby": {
                            "type": "string",
                            "enum": ["date", "count", "name"],
                            "description": "Field to sort by.",
                        },
                    },
                },
            ),
            Tool(
                name="search_users",
                description="Search Gelbooru users by name or name pattern.",
                inputSchema={
                    "type": "object",
                    "properties": {
                        "name": {
                            "type": "string",
                            "description": "Exact username to search for.",
                        },
                        "name_pattern": {
                            "type": "string",
                            "description": "Wildcard username search (SQL LIKE syntax).",
                        },
                        "limit": {"type": "integer", "default": 20, "minimum": 1, "maximum": 100},
                        "pid": {"type": "integer", "default": 0},
                    },
                },
            ),
            Tool(
                name="get_comments",
                description="Retrieve comments for a specific Gelbooru post.",
                inputSchema={
                    "type": "object",
                    "properties": {
                        "post_id": {
                            "type": "integer",
                            "description": "The post ID whose comments you want to retrieve.",
                        },
                    },
                    "required": ["post_id"],
                },
            ),
            Tool(
                name="get_character_tags",
                description=(
                    "Given a character name (e.g. 'misty_(pokemon)'), fetches the top "
                    "highest-scored general/solo posts across multiple pages and returns "
                    "the most frequently occurring tags split into three semantic buckets: "
                    "eye colour/shape, hair colour/style, and other character traits. "
                    "Each tag includes a frequency score. Results are cached to disk for 24 hours."
                ),
                inputSchema={
                    "type": "object",
                    "properties": {
                        "character_name": {
                            "type": "string",
                            "description": (
                                "The Gelbooru tag for the character, e.g. 'misty_(pokemon)', "
                                "'rem_(re:zero)', 'saber_(fate)'. Use underscores as Gelbooru does."
                            ),
                        },
                        "max_images": {
                            "type": "integer",
                            "description": (
                                "How many top-scored posts to analyse across all pages "
                                "(default 300). More images = slower but more reliable results. "
                                "Fetched in pages of 100."
                            ),
                            "default": 300,
                            "minimum": 10,
                        },
                    },
                    "required": ["character_name"],
                },
            ),
            Tool(
                name="build_prompt",
                description=(
                    "Given a character name, returns a ready-to-use image-generation prompt "
                    "string like 'misty (pokemon), green eyes, orange hair, side ponytail, ...'. "
                    "Internally calls get_character_tags with caching, then assembles the prompt "
                    "with tags ordered by frequency (eye → hair → other)."
                ),
                inputSchema={
                    "type": "object",
                    "properties": {
                        "character_name": {
                            "type": "string",
                            "description": (
                                "The Gelbooru tag for the character, e.g. 'misty_(pokemon)'. "
                                "Use underscores as Gelbooru does."
                            ),
                        },
                        "max_images": {
                            "type": "integer",
                            "description": "Posts to analyse (default 300). Cached after first fetch.",
                            "default": 300,
                            "minimum": 10,
                        },
                        "include_other": {
                            "type": "boolean",
                            "description": (
                                "Whether to include non-eye/hair tags (clothing, accessories, etc.) "
                                "in the prompt. Default true."
                            ),
                            "default": True,
                        },
                    },
                    "required": ["character_name"],
                },
            ),
        ]
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the 'last_id' parameter for pagination-like behavior but fails to describe critical traits such as authentication needs, rate limits, error conditions, or the format/scope of returned data (e.g., are all deleted posts returned or only user-accessible ones?).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two sentences that directly address the tool's function and a key parameter. It is front-loaded with the core purpose and avoids any redundant or unnecessary wording, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (retrieving deleted data with pagination), lack of annotations, and no output schema, the description is incomplete. It misses essential context like what 'deleted posts' entails (e.g., soft vs. hard deletion, timeframes), behavioral constraints, and output details, leaving significant gaps for agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (only 'last_id' has a description in the schema). The description adds meaning by explaining 'last_id' usage ('get everything deleted above that post ID'), which clarifies its pagination role. However, it doesn't address the 'limit' parameter at all, leaving half the parameters without semantic context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Retrieve') and resource ('deleted posts'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'search_posts' by focusing specifically on deleted content, though it doesn't explicitly contrast with all siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'search_posts' or 'get_comments'. It mentions a parameter usage ('Pass last_id...') but offers no context about appropriate scenarios, prerequisites, or exclusions for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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