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Guild Wars 2

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

A4.8/5.0
Behavior5/5

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

Adds significant behavioral context beyond annotations: mentions embedding model (BGE-base-en), chunking (500-char overlapping windows), character cap (200K chars) with truncation flag, and that passages include offsets for verification. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is relatively long but densely informative. Each sentence serves a purpose: purpose, when to use, how it works, return info, pairing with other tools. Well-structured and front-loaded.

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?

No output schema, but description fully explains return values: 'top-N passages with character offsets and similarity scores.' Also covers pairing with other tools, limitations (200K chars), and internal details (chunking). Completely adequate for agent to use correctly.

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%, so baseline is 3. The description adds value by explaining the text parameter context ('text you already pulled'), providing query examples, and clarifying the limit default and range. This goes beyond the schema 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?

Clearly states it performs semantic search inside a fetched record. Distinguishes from sibling tools like ask_pipeworx_grounded by specifying it searches inside an already-fetched text.

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: 'Use when the record is too big to cram into the prompt.' Also provides alternative: 'Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document.'

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

C2.8/5.0
Disambiguation2/5

The set mixes two unrelated domains (Guild Wars 2 endpoints and a broad Pipeworx data-research suite), and within each there are near-duplicates: ask_pipeworx vs ask_pipeworx_beta are functionally identical, commerce_prices vs guild_wars_2_item_price vs commerce_listings overlap on Trading Post data, and ask_pipeworx/ask_pipeworx_grounded/deep_research all route questions to the same source catalog. An agent could easily select the wrong tool.

Naming Consistency3/5

Names are all snake_case and readable, but there is no consistent pattern: some are bare nouns (achievements, currencies, quaggans, worlds, build), some are verb_noun (resolve_entity, validate_claim, generate_llms_txt), some are ask_* (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and some are compound names (polymarket_kalshi_spread, guild_wars_2_item_price). Minor deviations would be fine, but this is a genuine mix of conventions.

Tool Count2/5

42 tools is far beyond the well-scoped range, and the majority are unrelated to the 'Guild Wars 2' server name (only ~11 tools are GW2 API endpoints; the rest are Pipeworx data-research/meta tools). This feels like two or three servers merged into one.

Completeness2/5

For a Guild Wars 2 server, the coverage is thin: it has items, prices, achievements, worlds, and WvW, but no recipes, guilds, characters, skills, maps, or PvE content. For the broader data-research domain implied by most tools, the surface is sprawling but still lacks depth in several areas. The result is a set that is neither complete for GW2 nor coherently scoped for anything else.

Resources