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Wikipathways

by io.github.pipeworx-io

Deep Research

deep_research
Read-onlyIdempotent

ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1498 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,732 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a hop field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoHow many facets to research in parallel: quick=3 (single hop), standard=3 (default; adds a gap-recovery hop that re-angles unanswered facets + a contradictions[] scan across findings), thorough=6 (paid; adds a full iterative hop that chases leads + recovers gaps, plus the contradictions[] scan).
questionYesThe research question, in natural language. Broad/multi-part is fine — decomposition is the point.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses account requirements, paid-tier limits, 15-90s latency, facet decomposition, parallel routing, findings-packet contents, gaps[] behavior, contradictions[], citation fetchability, and semantic excerpting. This is rich behavioral context and does not contradict the annotations.

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 long but dense with operational information: auth, scope, alternatives, output contract, depth semantics, latency, and citation behavior. It front-loads the must-know account restriction and sibling fallback before explaining tool mechanics, so 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?

With no output schema present, the description supplies the missing contract: verbatim evidence, confidence, source, fetched_at, pipeworx:// citations, gaps[], contradictions[], hop metadata, and latency. An agent has enough context to invoke the tool, choose a depth, and interpret results correctly.

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

Parameters3/5

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

Schema coverage is 100%, and the input schema already documents both parameters, including the hop behavior and paid nature of each depth value. The description restates and illustrates the question-shape guidance with examples, but it does not materially extend the schema's parameter semantics beyond what is already present.

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's purpose: 'Grounded multi-source research across Pipeworx's 1498 STRUCTURED data sources ... in ONE call' and explicitly contrasts it with open-web search. It gives concrete example queries and names ask_pipeworx as the alternative for simple lookups, so an agent can reliably differentiate this tool from siblings.

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 gives explicit when-to-use and when-not-to-use guidance: use ask_pipeworx if not signed in or for a single lookup, and use deep_research for broad/multi-part questions over structured data. It also explains depth selection and the paid constraint on 'thorough', leaving little room for mis-selection.

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 is severely mismatched: only 3 of 34 tools (get_pathway, list_pathways, search_pathways) relate to WikiPathways while the rest form overlapping Pipeworx/Polymarket families (ask_pipeworx vs ask_pipeworx_beta vs ask_pipeworx_grounded; multiple polymarket_* tools) with unclear boundaries and overlapping purposes.

Naming Consistency2/5

Naming conventions are highly inconsistent: product-specific names (pipeworx_feedback, pipeworx_trending), generic memory verbs (remember, recall, forget), and mixed snake_case patterns with no unifying verb_noun structure. The names do not reflect the WikiPathways domain at all.

Tool Count1/5

34 tools is far too many for a WikiPathways server, which only needs a handful of pathway-related operations. Nearly all tools belong to unrelated domains (SEC, FDA, Polymarket, npm, etc.), making the set feel bloated and unfocused.

Completeness1/5

For the stated WikiPathways purpose, only get, list, and search are present—no create, update, or delete operations—leaving obvious lifecycle gaps. The extensive non-WikiPathways tools do not contribute to the server's apparent domain coverage and create dead ends for agents expecting pathway management.

Resources