PokerInk Poker Tools

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

With no annotations, the description carries the full behavioral burden. It accurately discloses the operation is a read/analysis and specifies the output granularity (category, label, draws, out counts). However, it does not reveal the return structure (how made hand vs. draws are formatted), edge cases (e.g., duplicate cards, 3 vs 5 card board handling), or how overlapping draws are reported. Core behavior is disclosed, but output-format and boundary details are absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence, zero filler. The verb and scope lead immediately, followed by a colon-delimited enumeration of outputs. Every clause earns its place, and the length is proportionate to the information being conveyed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 2-parameter tool with no output schema and no annotations, the description covers the essential selection and invocation facts: inputs (schema-covered), scope (3-5 card board), and outputs (made hand + draws with out counts). The minor gap — no explicit description of the result structure — is softened because the agent can infer the output from the enumerated elements. Slightly above adequate.

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

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

Schema coverage is 100%, with both 'hand' and 'board' documented with formats and examples in the schema, so the baseline is 3. The description reinforces the 3-5 card board constraint but adds no new parameter-level semantics — it explains what the analysis produces rather than adding meaning to the inputs. The schema already carries the load, so no penalty and no bonus.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Read') and resource ('one Texas Hold'em hand'), then enumerates the exact outputs: the made hand (category and label) and every draw with its out count. This precision distinguishes it from siblings calculate_equity (numeric equity) and calculate_pot_odds (odds comparison) without needing to inspect their schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the input preconditions explicit — a hand and a 3-5 card board — which tells the agent when this tool applies (analyzing a board that has already run out). It clearly implies use for structural hand evaluation as opposed to the numeric outputs of its siblings, though it never names those alternatives or states explicit exclusions. The context is clear but the routing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries full responsibility and does so well: it discloses exact enumeration for Hold'em, deterministic 200,000-board sampling for preflop Omaha, the ±0.2 percentage point precision, and reproducibility. This is substantial behavioral detail beyond the raw schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences deliver the core purpose, game variants, algorithm behavior, precision, and output values without redundant phrasing. The most critical decision-driving information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description states the return values (win, tie, total equity percentages), input constraints (2-4 hands, 0-5 board cards), and game-specific rules, covering what an agent needs to invoke it correctly. No output schema exists, so the description's explicit output summary is especially valuable.

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

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

The input schema already covers game, board, and hands, and the description adds important semantics such as the difference between exact postflop enumeration and sampled preflop evaluation, plus the 'best two play' rule for Omaha. It does not restate every parameter, but it meaningfully supplements the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource: calculating equity for Texas Hold'em or Pot Limit Omaha across 2-4 hands and 0-5 community cards, with explicit output values. It clearly distinguishes this from siblings like calculate_pot_odds by focusing on equity percentages rather than pot odds.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use the tool (equity calculation for specific hands/boards) and elaborates on game-specific behavior such as Omaha requiring four-card hands and best-two-play rules. It does not explicitly state when not to use this tool or name alternative tools, so it misses the top score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden. It discloses the return values, the exact break-even formula, the precise counting of unseen cards, and a known pitfall (bet/(pot+bet) overstates). It does not discuss error handling or edge cases, but the behavioral core is transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Every sentence earns its place: the first sentence states purpose and outputs, the middle sentences give the exact formula and common errors, and the final sentence connects the tool to analyze_hand. The guidance is dense but highly relevant and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, outputs, parameter semantics, and the key workflow with analyze_hand. It is nearly complete, but it does not address how calculate_equity differs or when that sibling should be used instead, which leaves a small contextual gap.

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

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

Even though schema coverage is 100%, the description adds significant semantic value: it clarifies pot is before the bet, explains why the break-even share is call divided by (pot + bet + call), defines street in terms of remaining cards, and notes implied_extra lowers required equity. This goes well beyond the schema's simple field descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific, decision-oriented statement: 'Decide whether calling a bet is profitable,' followed by exactly what the tool returns. It also distinguishes the tool from doing manual arithmetic or applying the Rule of 2 and 4, and names analyze_hand as the complementary tool for out counts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to use this tool instead of doing the arithmetic and to pair it with analyze_hand for the out count. It implies when to call versus avoid it, though it does not explicitly contrast with the sibling calculate_equity or state when calculate_equity would be preferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.