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Podcastindex

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

A5/5.0
Behavior5/5

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

Discloses retrieval method (BGE-base-en embeddings, cosine similarity, 500-char windows), output structure (passages with offsets and scores), and truncation behavior (200K char cap with flagging). This goes well beyond the annotations (readOnlyHint, idempotentHint) and fully informs the agent.

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 a single, well-structured paragraph that front-loads the core action and packs all essential information without redundancy. Every sentence earns its place.

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?

Despite having no output schema, the description details return values (passages with offsets and scores), truncation behavior, and embedding model. This makes the tool fully self-contained and actionable.

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

Parameters5/5

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

Schema coverage is 100%, but description adds value by explaining text as a fetched record, query as natural language with examples, and limit as max passages. This semantic enrichment helps the agent craft correct invocations.

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 single fetched record, using verbs like 'search INSIDE' and examples (SEC filing, article). It distinguishes itself from sibling tools by focusing on document-level retrieval rather than cross-document search, and even suggests a 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 tells when to use: 'when the record is too big to cram into the prompt.' Also describes how it pairs with ask_pipeworx_grounded for grounded answers. Provides clear context and alternatives, making it easy for an agent to decide.

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

All Podcastindex toolsInspect
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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but ask_pipeworx and ask_pipeworx_grounded overlap (one is grounded), and bet_research/validate_claim/compare_entities/entity_profile all query Pipeworx data with different intents, which could cause confusion.

Naming Consistency4/5

Names are consistently lower_snake_case and mostly follow a verb_noun pattern (e.g., search_podcasts, get_podcast, list_subscriptions). A few compound names like pipeworx_feedback and polymarket_arbitrage deviate slightly but remain readable.

Tool Count2/5

30 tools is excessive for a server named 'Podcastindex'. It aggregates unrelated domains (podcasts, Pipeworx queries, Polymarket, memory, etc.), making it feel like a kitchen sink rather than a focused tool set.

Completeness3/5

For podcasts, the tool set covers search, metadata, episodes, and trending but lacks subscription management. For the broader Pipeworx domain, ask_pipeworx and discover_tools provide wide access, but specific gaps exist (e.g., no direct SEC filing query). Overall, the surface is broad but uneven.

Resources