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Glama

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".

TDQS

A4.9/5.0
Behavior5/5

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

Goes beyond annotations by detailing embedding model, window size, truncation at 200K chars with flagging, and output format (character offsets, similarity scores). No contradictions.

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?

Concise, front-loaded core statement, each sentence adds value. No wasted text; covers purpose, usage, and technical details efficiently.

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?

Fully explains input/output behavior despite no output schema; includes truncation handling and integration with sibling tool. Complete for agent understanding.

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

Parameters4/5

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

Schema covers all parameters with descriptions; description adds value with example queries and context for the 'text' max size. Slightly exceeds baseline of 3.

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, with specific examples (SEC 10-K) and differentiates from sibling by mentioning pairing with ask_pipeworx_grounded.

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?

Explicitly explains when to use (record too large for prompt) and references an alternative (ask_pipeworx_grounded). Provides clear context for appropriate usage.

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

B3.3/5.0
Disambiguation1/5

The tool set includes multiple overlapping tools for predictions (bet_research, polymarket_arbitrage, polymarket_edges, etc.) and data lookups (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and mixes blockchain tools with unrelated services, making it difficult for an agent to select the correct tool.

Naming Consistency1/5

Tool names follow no consistent pattern: some use verb_noun (get_address, list_chains), others are multi-word phrases (ai_visibility_check, compare_entities), and styles mix snake_case and camelCase erratically.

Tool Count2/5

With 39 tools, the surface is bloated for a blockchain explorer. Many tools are unrelated to blockchain, inflating the count well beyond what is necessary for the server's stated purpose.

Completeness1/5

The server is named 'Blockscout' but includes mostly non-blockchain tools, leaving the blockchain domain severely incomplete. Even the blockchain-specific tools miss common operations like event logs or internal transactions.