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Bhagavad Gita

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

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint; description adds rich behavioral detail: walks the order book ladder, returns specific fields, explains basket fill behavior, identifies thin legs and directional risk. No contradiction and substantial added context.

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 long but well-structured with clear sections (REQUIRES, SINGLE-MARKET, BASKET) and uses bold for key terms. Every sentence adds value, though it could be slightly tightened. Still efficient for the complexity.

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?

Despite lacking an output schema, the description lists all return fields for both modes comprehensively. It also explains defaults, ranges, and risk warnings, making it fully self-contained for an agent to understand inputs and outputs.

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 description coverage is 100%, but the description adds extra semantics: explains default auto logic for side in basket mode, size_usd interpretation differences, and clamp ranges. This goes beyond the basic schema descriptions.

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 explicitly states the tool performs a 'realizable-vs-theoretical edge check against live CLOB order-book depth', with clear single-market and basket modes. It distinguishes from siblings by name-dropping polymarket_arbitrage and polymarket_edges and specifying when to use this tool before them.

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 provides explicit usage guidance: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500'. It explains the rationale (partial fills risk, uncapturable theoretical overround) and mentions alternatives implicitly.

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
Disambiguation4/5

Individual tools have detailed descriptions and mostly distinct purposes, but the mix of domains (scripture, finance, data lookup) could confuse an agent about which tool to choose for a given task. However, within each subdomain, tools are clearly differentiated.

Naming Consistency2/5

Tool names follow no consistent pattern: some are verb_noun (ask_pipeworx, compare_entities), some are noun_verb (entity_profile, recent_changes), and some are single verbs (forget, recall). The mix of snake_case with varied starting parts makes naming unpredictable.

Tool Count1/5

With 23 tools but only 3 related to the server's stated purpose (Bhagavad Gita), the tool count is severely mismatched. The vast majority belong to data analytics and finance, making the set feel bloated and mis-scoped.

Completeness1/5

For a Bhagavad Gita server, only list_chapters, get_chapter, and get_verse are provided, missing obvious features like search, commentary comparison, or multiple translations. The other tools are irrelevant to the domain, leaving it extremely incomplete.