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Malwarebazaar

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 provide readOnlyHint, idempotentHint, etc. The description adds valuable behavioral context: it walks the order-book ladder, returns specific fields (top_of_book, vwap_fill_price, slippage_pp, etc.), and for basket mode details per-leg fill detail, thin_legs, forced_directional_risk. 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?

The description is relatively long but well-structured using uppercase headings (SINGLE-MARKET, BASKET) and bullet-style lists. Every sentence provides essential information, though a bit more conciseness could be achieved without losing clarity.

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?

Given the tool's complexity (dual modes, multiple return fields, no output schema), the description is exceptionally complete. It covers required parameters, return values for both modes, defaults, warnings about risks, and even implications for partial fills. No gaps identified.

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

Parameters5/5

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

Schema description coverage is 100%, but the description adds significant meaning beyond the schema: it explains the difference between single-market and basket modes, the interpretation of size_usd (spend vs target proceeds vs settlement notional), default side logic for basket, and clamp ranges. This information is critical for correct usage.

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: a realizable-vs-theoretical edge check against live CLOB order-book depth. It distinguishes between single-market and basket modes, and explains what each mode returns, making it 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 when to use this tool: before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or polymarket_edges trade above ~$500. It also explains that theoretical overround on thin books is not capturable, implying when not to rely on theory alone, and highlights risks like partial basket fills converting arb into unhedged directional positions.

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

A3.5/5.0
Disambiguation2/5

Several tools are near-duplicates: ask_pipeworx_beta is described as currently identical to ask_pipeworx, and ask_pipeworx_grounded is the same router with extra verification. Malware sample searches also overlap across search_family, search_tag, search_signature, and recent_samples, while ai_visibility_check is wrapped by scan_competitor_ai_presence.

Naming Consistency3/5

The set mostly uses snake_case and verb-first names like get_sample_info and validate_claim, which is helpful. However, conventions are mixed across ask_pipeworx*, polymarket_*, pipeworx_*, search_*, and noun-style names like recent_samples and entity_profile, so there is no single predictable pattern.

Tool Count2/5

36 tools is already over the comfortable range, but the bigger issue is that the server is named Malwarebazaar while only about five tools actually deal with malware. The remaining tools belong to an unrelated data-research, prediction-market, memory, and subscription platform, making the count inappropriate for the server's apparent purpose.

Completeness2/5

For the MalwareBazaar domain, the set covers metadata lookups and filtered sample searches but lacks sample submission, retrieval, or deeper analysis workflow. The rest of the tool surface targets unrelated domains, so there is no coherent, complete lifecycle for either malware intelligence or the broader feature set.

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