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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 1499 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 5,738 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

A4.8/5.0
Behavior5/5

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

Despite readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, the description carries far beyond annotations: account/tier gating ("depth:'thorough' needs a paid plan"), latency windows ("Expect 15-60s (thorough ... up to ~90s)"), the never-fabricates guarantee ("explicit gaps[] ... never invented"), semantic excerpting ("not head-truncated"), resolvable citation_uri behavior, and the breaking-news limitation yielding empty gaps[]. None of this is derivable from 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?

Every sentence earns its place — auth gate, fallback routing, core mechanism, caps/limitations, depth semantics, return packet, latency, citation resolvability. It is appropriately sized for a highly complex tool and front-loaded with the critical account requirement before anything else. Minor structural deduction: it is a single dense wall of text with no paragraph breaks or list formatting, and the depth behaviors are partially restated from the schema.

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, the description correctly shoulders the burden of explaining return values — findings packet fields (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, hop, citation_uri, gaps[], contradictions[]) are all enumerated. It also covers auth/signup URL, paid tiers, latency, error/edge behavior (breaking news → mostly empty gaps), and sibling routing. For a tool with this complexity (2 params, 3 depth modes, massive parallel routing, no output schema), nothing decision-relevant is missing.

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% (both params fully documented), so baseline is 3. The description adds genuine value beyond the schema: the paid-plan gate tied to depth, per-depth latency expectations, and prose clarification that "standard" recovers gaps while "thorough" chases first-pass leads. The question param needs no elaboration since it explicitly accepts natural-language multi-part input.

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 specific verb and resource: "Grounded multi-source research across Pipeworx's 1497 STRUCTURED data sources ... in ONE call," with concrete mechanism (decomposes into facets, routes to 5,724 tools in parallel) and return format. It explicitly differentiates from siblings: "this is NOT open-web search" and contrasts with ask_pipeworx ('For a single lookup use ask_pipeworx (one LLM call, not many)').

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?

Gives explicit when/when-not conditions and names alternatives: "If you are not signed in, use ask_pipeworx instead — it works on every tier," "Best for broad/multi-part questions over structured data," and "For BREAKING or colloquial CURRENT-NEWS ... prefer ask_pipeworx — it routes to live news APIs; deep_research returns mostly empty gaps[]." The conditions map directly to tool 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

A3.6/5.0
Disambiguation2/5

Multiple tools occupy the same conceptual space: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all answer 'what can this server do' or 'look this up' in overlapping ways. The Polymarket suite (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) and the memory trio (remember, recall, forget) also create boundary confusion despite long descriptions.

Naming Consistency2/5

Naming is a mixed bag: some tools are imperative verbs (check_ip, forget, remember, validate_claim), some are bare nouns or adjectives (list, recent, aggressive), and many are noun compounds (entity_profile, polymarket_edges, pipeworx_trending). No consistent verb_noun or domain-prefix pattern holds across the set.

Tool Count2/5

35 tools is excessive for a server ostensibly named Feodotracker, whose core blocklist surface is only four tools (list, recent, aggressive, check_ip). The rest is a sprawling collection of unrelated Pipeworx, Polymarket, memory, subscription, and utility features that would be better split into separate servers.

Completeness3/5

The core blocklist domain is minimally covered: you can list, filter by family/status, check an IP, and see recent additions, which covers basic read-only use. However, there are notable gaps and dead ends, such as no historical lookup beyond recent hours and no per-IP detail beyond membership, while the bundled Pipeworx/Polymarket features are thorough but make the overall surface feel scattershot.