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Last Fm

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".

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, etc.), the description reveals embedding model (BGE-base-en), chunking strategy (500-char overlapping windows), similarity metric (cosine), character limit (200K chars with truncation and flagging), and that each passage carries an offset for verification. This is rich behavioral context.

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 comprised of two well-structured sentences. The first defines the core functionality, and the second provides usage guidance and technical details. Every sentence is informative and there is no redundant or extraneous content.

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?

The description explains the return format (passages with offsets and scores), truncation behavior, and the tool's role in a multi-step workflow. Given there is no output schema, this is sufficient for an agent to understand inputs, outputs, and boundary conditions. It fully covers the tool's complexity.

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 coverage is 100% with descriptions provided for all three parameters. The description adds value by reinforcing constraints (e.g., 'max ~200K chars' for 'text'), providing default values ('limit' default 5), and giving natural-language examples for 'query' (e.g., 'supply-chain risk'). This enhances the schema beyond basic descriptions.

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 clearly states the tool performs semantic search inside a given text, returning relevant passages with offsets and scores. It distinguishes itself from siblings by explicitly mentioning 'ask_pipeworx_grounded' as a complementary tool and highlighting the benefit of saving context for large records.

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?

The description provides explicit guidance on when to use the tool: 'Use when the record is too big to cram into the prompt.' It also explains the integration pattern with 'ask_pipeworx_grounded', detailing how to fetch and then ground over relevant passages. No alternative tools are listed, but the pairing is clear.

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
Disambiguation2/5

Many tools have overlapping purposes, especially the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and the Polymarket cluster (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). Additionally, discover_tools and suggest_questions both serve as discovery/onboarding tools, and ai_visibility_check vs scan_competitor_ai_presence are closely related. While descriptions are detailed, the boundaries between these tools are unclear, causing potential misselection.

Naming Consistency4/5

All tool names use lowercase snake_case with no camelCase or mixed styles. The naming follows a mostly consistent verb_noun or data_subject pattern (e.g., ask_pipeworx, list_subscriptions, validate_claim, artist_info, recent_alerts). Minor deviations exist, such as recent_alerts and user_top_tracks not beginning with a verb, but the overall pattern is predictable and readable.

Tool Count2/5

40 tools is far too many for a server nominally about Last.fm; only 9 tools actually relate to its stated purpose. The remaining 31 tools cover unrelated domains (Pipeworx data routing, Polymarket betting, memory, subscriptions, etc.), making the set bloated and unfocused. Many tools are near-duplicates (ask_pipeworx, _beta, _grounded; four different polymarket_* analysis tools), inflating the count without adding distinct value.

Completeness2/5

Even within the Last.fm domain, the tool surface is incomplete: there is no artist search, album search, user profile info, recent scrobbles, loved tracks, or music recommendations. The unrelated Pipeworx/Polymarket tools, while individually comprehensive for their own domains, do not compensate for the lack of core Last.fm functionality given the server's stated purpose. The overall set is a fragmented mixture that leaves significant gaps for what the server name promises.

Resources