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dnd5e

by io.github.pipeworx-io

Search Within a Source

search_within
Read-onlyIdempotent

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe document text to search inside (max ~200K chars).
limitNoMax passages to return (1-20, default 5).
queryYesNatural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/idempotent, and the description adds no contradictions. It discloses concrete mechanics: BGE-base-en embeddings, 500-char overlapping windows, 200K char cap with truncation flagging, and character offsets for quote verification.

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?

Three sentences, front-loaded with 'Semantic search INSIDE a fetched record.' Each clause adds value: function, use case, and implementation detail – no filler.

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

Completeness5/5

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

For a 3-param tool with no output schema, the description covers input requirements, output shape (passages with offsets and similarity), usage guidance, and technical constraints. The annotation set already covers safety and idempotency, so no gaps remain.

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 descriptions cover all three parameters (text, limit, query) with max length, range, default, and example. The description adds only contextual guidance on what text to pass (SEC filings, articles) but doesn't go beyond the schema's parameter semantics.

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

Purpose5/5

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

The description opens with 'Semantic search INSIDE a fetched record' – a specific verb+resource statement. It distinguishes itself from sibling tools by framing it as a post-fetch operation that returns passages with offsets, rather than acting as a general ask tool.

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

Usage Guidelines5/5

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

It explicitly states 'Use when the record is too big to cram into the prompt' and explains context-saving benefits. It also names ask_pipeworx_grounded as a complementary tool, providing a clear alternative workflow.

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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TDQS

B3.4/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as the three ask_pipeworx variants, the memory tools (remember/recall/forget), and the subscription management tools. Additionally, the D&D tools are mixed with a large set of unrelated tools, causing confusion between domains.

Naming Consistency2/5

Naming conventions are inconsistent: some tools follow verb_noun pattern (e.g., get_class, list_spells), while others use descriptive noun phrases (e.g., ai_visibility_check, polymarket_arbitrage). There is no clear, predictable pattern across the set.

Tool Count2/5

With 35 tools, the count is high for a server ostensibly focused on D&D 5e. The inclusion of many unrelated tools from the Pipeworx ecosystem makes the set feel bloated and unfocused for the intended domain.

Completeness1/5

For the D&D 5e domain, only 4 tools exist (get_class, get_monster, get_spell, list_spells), which is severely incomplete. The remaining tools cover other domains, but they do not serve the server's primary purpose, leaving obvious gaps in functionality.

Resources