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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

A4.5/5.0
Behavior5/5

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

Discloses embedding model, similarity metric, window size, character cap (200K), truncation behavior, and that passages include offsets. Annotations confirm safe, read-only, idempotent behavior; description adds valuable technical details beyond annotations.

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, no filler. Front-loaded with the core action, then use-case, then technical details. Every sentence adds value.

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 tool with 3 params, no output schema, and annotations present, the description fully covers purpose, usage, technical limitations, and integration pattern. No gaps for agent decision-making.

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 coverage is 100%; schema already describes each parameter. Description adds example queries and mentions truncation flag but does not substantially enhance semantic understanding beyond schema.

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?

Clearly states it performs semantic search inside a fetched record, explicitly distinguishing from siblings by mentioning it pairs with ask_pipeworx_grounded. The verb 'search within' and resource 'source' are specific.

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

Usage Guidelines4/5

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

Explicitly states when to use: when record is too big for prompt. Describes pairing with sibling tool. Lacks explicit when-not or alternatives to other search tools.

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

B3.1/5.0
Disambiguation4/5

Most tools have distinct purposes, especially within the Roblox and Pipeworx domains. However, the three variants of ask_pipeworx (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are very similar and could cause confusion, as could deep_research vs ask_pipeworx.

Naming Consistency3/5

Naming conventions are mixed: snake_case (user_followers_count), verb_noun with underscores (ask_pipeworx), and camelCase (recall, forget). Roblox tools follow a consistent 'user_' prefix, but Pipeworx tools lack a uniform pattern.

Tool Count2/5

41 tools is excessive for a server named 'Roblox'. The majority of tools are Pipeworx data utilities, which are unrelated to the server's apparent focus. This overloading undermines coherence.

Completeness3/5

Coverage within the Roblox domain is basic (user profiles, friends, games) but misses common features like asset details or group management. Pipeworx appears comprehensive for data lookups, but the overall set lacks unified domain completeness.