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Wikipathways

by io.github.pipeworx-io

Ask Pipeworx — Grounded

ask_pipeworx_grounded
Read-onlyIdempotent

Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 5,732 across 1498 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for question.
textNoAlias for question.
inputNoAlias for question.
queryNoAlias for question.
promptNoAlias for question.
questionYesYour question in natural language. Accepts query, q, prompt, text, input as aliases.

TDQS

A4.7/5.0
Behavior5/5

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

The description explains the refusal mechanism, the exact return shape, the possible refusal_reason values, and the extra LLM call cost. This goes well beyond the readOnlyHint annotations and tells the agent exactly what to expect behaviorally.

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 information-dense but every sentence earns its place: purpose, mechanism, return shape, refusal reasons, usage guidance, and cost trade-off. It is well-structured and front-loaded with the most important behavioral property.

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?

Even without an output schema, the description fully covers the return values, failure modes, usage context, and cost consideration. It gives an agent everything needed to decide whether to call this tool and how to interpret its results.

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?

The description does not add much parameter-level detail, but schema coverage is 100% and the schema already explains the 'question' parameter and all its aliases clearly. The description's mention of asking a natural-language question aligns with the schema but adds no new semantic 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 states a clear, specific purpose: a hallucination-resistant answer mode that extracts answers only from tool results. It also explicitly distinguishes itself from ask_pipeworx by noting the same routing but a stricter, grounded extraction behavior.

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?

It gives explicit guidance on when to use this tool: when answers will be quoted, cited, or acted on, and when facts must not be invented. It also says to prefer ask_pipeworx for casual lookups, providing a clear alternative and exclusion.

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