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W3c

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. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive. The description adds valuable behavioral details beyond annotations: embedding model (BGE-base-en), similarity metric (cosine), windowing (500-char overlapping windows), character limit (200K chars with truncation flag), and support for verifying verbatim quotes via offsets.

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?

Every sentence earns its place. The description is front-loaded with the core purpose, then provides usage context, pairing advice, and technical details. No redundancy or fluff, and it remains under three sentences of substantive 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?

Despite having no output schema, the description fully explains the return structure: top-N passages with character offsets and similarity scores. It also covers the 200K char limit and truncation behavior. For a search tool with three parameters, this is complete and leaves no gaps.

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 good descriptions for each parameter. The description adds further context: 'natural-language query' with examples, 'max ~200K chars' for text, and default/max for limit (1-20, default 5). This enriches the schema information.

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 fetched record' and returns top-N passages with character offsets and similarity scores. It distinguishes itself from siblings by explicitly naming ask_pipeworx_grounded as a complementary tool, and the title 'Search Within a Source' reinforces the specific action.

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?

The description provides concrete usage guidance: 'Use when the record is too big to cram into the prompt' and explains the benefit of saving context with passage offsets. It also pairs the tool with ask_pipeworx_grounded, but does not explicitly list when not to use it or alternative siblings.

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

A3.9/5.0
Disambiguation3/5

The three ask_pipeworx variants plus deep_research and validate_claim overlap heavily on the same routing capability — ask_pipeworx_beta is even explicitly identical to ask_pipeworx right now. The polymarket tools (arbitrage/edges/edge_tracker/fill_risk/kalshi_spread) form a second cluster with fuzzy boundaries, and ai_visibility_check vs scan_competitor_ai_presence overlap. However, most other tools (w3c_search, spec, remember/recall/forget, subscribe/unsubscribe) have clear distinct roles.

Naming Consistency3/5

Names are generally descriptive snake_case with recognizable prefix families (ask_pipeworx_*, polymarket_*, w3c_*), but verb usage is inconsistent: passive labels like ai_visibility_check and entity_profile sit alongside imperatives like recall, forget, subscribe, and resolve_. There's no uniform verb_noun or noun_pattern convention across the set.

Tool Count2/5

33 tools is over the heavy threshold, and the count is wildly mismatched to the server's claimed identity: the server is named 'W3c' yet only 2 of 33 tools (w3c_search, w3c_spec) relate to W3C. The remaining 31 form a sprawling Pipeworx data/prediction-market service that would justify its own server, making this aggregation incoherent.

Completeness3/5

For its actual purpose (broad data research + prediction markets), the surface is fairly complete: search, grounded answers, deep research, comparison, entity profiles, entity resolution, memory, subscriptions, and feedback cover the main workflows. But for the server's stated W3C purpose, only search and spec-detail exist with no broader standards tooling. The domain mismatch makes completeness hard to credit.

Resources