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Biostudies

by io.github.pipeworx-io

Polymarket Fill Risk

polymarket_fill_risk
Read-onlyIdempotent

Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of market (single-market mode) or event (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sideNoSingle-market: buy_yes | sell_yes | buy_no | sell_no (default buy_yes). Basket: sell_yes | buy_yes (default auto — sell if partition sum > 1, buy if < 1).
eventNoBasket mode: event slug or full polymarket.com URL — checks every leg of the partition.
marketNoSingle-market mode: market slug or full polymarket.com URL.
size_usdNoSingle-market: USD to spend (buys) or target proceeds (sells). Basket: settlement notional — shares per leg, each paying $1 at resolution. Default 1000, clamp 10–1,000,000.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark it as read-only and idempotent. The description adds behavioral details: it walks the order-book ladder, computes slippage, fillability, and returns a verdict. It also warns about partial basket fills converting arb into unhedged directional positions.

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?

Though lengthy, every sentence is necessary. Uses CAPS for emphasis on modes and key warnings. Front-loaded with purpose and requirements, then detailed mode-specific explanations.

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 enumerates all returned fields for both modes (top_of_book, vwap_fill_price, slippage_pp, etc.). Covers edge cases like thin legs and forced directional risk. Comprehensive given complexity.

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 descriptions. The description adds meaning: explains default side behavior in both modes, and the dual interpretation of size_usd ('USD to spend on buys, target proceeds on sells; basket mode: settlement notional'). This goes beyond the schema.

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 it is a 'Realizable-vs-theoretical edge check against live CLOB order-book depth,' distinguishing between single-market and basket modes. It is distinct from sibling tools like polymarket_arbitrage and polymarket_edges.

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 states 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500', providing clear context and alternatives.

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

A3.8/5.0
Disambiguation2/5

Several tools occupy nearly identical roles: ask_pipeworx and ask_pipeworx_beta are described as functionally identical right now, ask_pipeworx_grounded and deep_research are overlapping query modes, and ai_visibility_check / scan_competitor_ai_presence / discover_tools / suggest_questions all blur into discovery or visibility tasks. The two actual BioStudies tools are clear, but they are buried in a server dominated by Pipeworx meta-tools.

Naming Consistency3/5

All tool names use snake_case, and many follow a verb_noun shape such as search_studies, get_study, and discover_tools. However, the convention is inconsistent across the set: noun-first names like entity_profile and polymarket_edges, brand-prefixed names like pipeworx_feedback, and verb-first product names like ask_pipeworx all coexist, making the pattern harder to predict.

Tool Count2/5

33 tools is well into the too-many range, and the count is especially inappropriate for a server named Biostudies since only search_studies and get_study actually belong to that domain. The rest form a sprawling general-purpose data-research platform that appears to have been merged into one server without a clear scope.

Completeness3/5

For the BioStudies-specific surface, search_studies and get_study provide reasonable read-only coverage for the EBI archive. But as the broader research platform the other 31 tools imply, the set is hard to evaluate for completeness because most actual data access is delegated to Pipeworx's hidden 5,718 tools rather than exposed directly, leaving notable gaps in transparency and direct source-level control.

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